Home
Search results “Data mining tools twitter backgrounds”
Natural Language Processing (NLP) & Text Mining Tutorial Using NLTK | NLP Training | Edureka
 
40:29
** NLP Using Python: - https://www.edureka.co/python-natural-language-processing-course ** This Edureka video will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP. You will also learn about the different steps involved in processing the human language like Tokenization, Stemming, Lemmatization and much more along with a demo on each one of the topics. The following topics covered in this video : 1. The Evolution of Human Language 2. What is Text Mining? 3. What is Natural Language Processing? 4. Applications of NLP 5. NLP Components and Demo Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------------------- Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ --------------------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 61048 edureka!
Analyzing Network Data - GCDH Twitter Workshop
 
01:34:12
1st Part: "Prof. Bruns, Prof. Burguess & Dr. Woodford: Mapping Online Publics: New Methods for Twitter Research" The study of Twitter at large scale and in close to real time requires the development of new methodological approaches which are able to process, analyse, and visualise the 'big social data' which can be accessed through the Twitter API. The Mapping Online Publics project in the ARC Centre of Excellence for Creative Industries and Innovation (CCI) at Queensland University of Technology has developed a number of approaches to the study of short- and long-term Twitter publics, from analyses of the dynamics of ad hoc issue publics around natural disasters and political crises through the tracking of information flows and audience interests across mainstream and social media to the comprehensive mapping of the Australian Twittersphere. This presentation will outline the methodological approaches developed for this work, and reflect on the opportunities and challenges facing social media researchers. 2nd Part: "Robert Jäschke: Identifying and Analyzing Researchers on Twitter" For millions of users Twitter is an important communication platform, a social network, and a system for resource sharing. Likewise, scientists use Twitter to connect with other researchers, announce calls for papers, or share their thoughts. Filtering tweets, discovering other researchers, or finding relevant information on a topic of interest, however, is difficult since no directory of Twitter users with a scientific background exists. In this paper we present an approach to identify Twitter accounts of researchers and demonstrate its utility for the discipline of computer science. Based on a seed set of computer science conferences we collect relevant Twitter users which we can partially map to ground-truth data. The mapping is leveraged to learn a model for classifying the remaining users with high accuracy. To gain further insights into how Twitter is used by researchers, we perform an empirical analysis of the identified users and compare their age, popularity, influence, and social network. For more information and the slides of the presentations please visit http://www.gcdh.de/en/events/calendar-view/twitter-workshop-analyzing-network-data
Learn Data Science in 3 Months
 
11:14
I've created a 3 month curriculum to help you go from absolute beginner to proficient in the art of data science! This open source curriculum consists of purely free resources that I’ve compiled from across the Web and has no prerequisites, you don’t even have to have coded before. I’ve designed it for anyone who wants to improve their skills and find paid work ASAP, ether through a full-time position or contract work. You’ll be learning a host of tools like SQL, Python, Hadoop, and even data storytelling, all of which make up the complete data science pipeline. Curriculum for this video: https://github.com/llSourcell/Learn_Data_Science_in_3_Months Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Week 1 - Learn Python - EdX https://www.edx.org/course/introduction-python-data-science-2 - Siraj Raval https://www.youtube.com/watch?v=T5pRlIbr6gg&list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU Week 2 - Statistics & Probability - KhanAcademy https://www.khanacademy.org/math/statistics-probability Week 3 - Data Pre-processing, Data Vis, Exploratory Data Analysis - EdX https://www.edx.org/course/introduction-to-computing-for-data-analysis Week 4 - Kaggle Project #1 Week 5-6 - Algorithms & Machine Learning - Columbia https://courses.edx.org/courses/course-v1:ColumbiaX+DS102X+2T2018/course/ Week 7 - Deep Learning - Part 1 and 2 of DL Book https://www.deeplearningbook.org/ - Siraj Raval https://www.youtube.com/watch?v=vOppzHpvTiQ&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3 Week 8 - Kaggle Project #2 Week 9 - Databases (SQL + NoSQL) - Udacity https://www.udacity.com/course/intro-to-relational-databases--ud197 - EdX https://www.edx.org/course/introduction-to-nosql-data-solutions-2 Week 10 - Hadoop & Map Reduce + Spark - Udacity https://www.udacity.com/course/intro-to-hadoop-and-mapreduce--ud617 - Spark Workshop https://stanford.edu/~rezab/sparkclass/slides/itas_workshop.pdf Week 11 - Data Storytelling - Edx https://www.edx.org/course/analytics-storytelling-impact-1 Week 12- Kaggle Project #3 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hiring? Need a Job? See our job board!: www.theschool.ai/jobs/ Need help on a project? See our consulting group: www.theschool.ai/consulting-group/ Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 335248 Siraj Raval
Guide To Sentiment Analysis On Twitter Popular Trends Using R | By Expert From Amsterdam University
 
39:27
Overview: This is a tutorial on how to do sentiment analysis. Sentiment analysis is the process of identifying opinions expressed in text to determine the writer's attitude towards the topic. As an example, this tutorial has been formulated around doing sentiment analysis of twitter popular trends using R with a database of 3000 entries of 2016 US elections. Topics covered: 1. Data Mining 2. Text Mining 3. Corpus Analysis 4. Bag of words Analysis 5. Word2Vec Analysis 6. How to extract data from Social Media APIs 7. Word Sense Disambiguation algorithm 8. Polarities in Descriptive analysis (positive, negative, & neutral) 9. Predictive Accuracy rates using Dependency Grammer 10. Vector Notation of Diplomatic Letters & Sentences 11. Cross-Validation Method to find K value in KNN (sentiment classification) Click the subscribe button below the video to get updates on videos related to data science and machine learning! About our data science course: Gain a hands-on-experience in using various tools of analytics, including ‘R’, SQL and Tableau while gaining an insight into the real-world cases with this instructor-led live online classes. This data science using ‘R’ course provides a project-based practical learning experience for learners from all academic and professional backgrounds. Why use R for Data Science? R is a data analysis software that can be used for statistical analysis, data visualization and predictive modelling. Statistical methods are easier to implement in R. Often the programming language is used for research in statistics as most of the recently developed techniques can be carried out through R. In addition, R is free of cost and has an improves numerical accuracy as compared to other languages. If you have any queries regarding this video and our course, please comment below and our experts will get back to you. For more information on data science courses please visit http://www.skillanalytica.com/ Please follow us on our social media handles for more updates: https://www.facebook.com/Skillanalytica/ https://twitter.com/Analyticaskill https://www.instagram.com/skillanalytica/
Views: 125 Skill Analytica
Webinar: Visual Tools for Big Data Network Analysis
 
27:15
Shaunna Morrison, Carnegie Institution for Science (USA) Ahmed Eleish, Rennselear Polytechnic Institute (USA) Discover how to turn large data sets into dynamic visualizations that show network connections.
Views: 650 Deep Carbon
Stemming And Lemmatization Tutorial | Natural Language Processing (NLP) With Python | Edureka
 
12:45
( **Natural Language Processing Using Python: - https://www.edureka.co/python-natural-language-processing-course ** ) This video will provide you with a detailed and comprehensive knowledge of the two important aspects of Natural Language Processing ie. Stemming and Lemmatization. It will also provide you with the differences between the two with Demo on each. Following are the topics covered in this video: 0:46 - Introduction to Big Data 1:45 - What is Text Mining? 2:09- What is NLP? 3:48 - Introduction to Stemming 8:37 - Introduction to Lemmatization 10:03 - Applications of Stemming & Lemmatization 11:04 - Difference between stemming & Lemmatization Subscribe to our channel to get video updates. Hit the subscribe button above https://goo.gl/6ohpTV ----------------------------------------------------------------------------------------------- Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ----------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learnt content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
Views: 5656 edureka!
Data Analyst Roles & Responsibilities | Data Analyst Skills | Data Analytics Certification | Edureka
 
06:21
( ** Data Analyst Master's Program: https://www.edureka.co/masters-program/data-analyst-certification ** ) This Edureka tutorial on "Data Analyst Roles and Responsibilities" will explain, what are the Roles and Responsibilities of a Data Analyst in the Industry. It also explains who is a Data Analyst and what does it takes to become one. Following topics are included in the video: 1:51 Determine Organizational Goals 2:07 Mining Data 2:35 Data Cleaning 3:07 Analyzing Data 3:42 Pinpointing Trends and Patterns 4:14 Creating Reports with Clear Visualizations 4:54 Maintaining Databases and Data Systemtems -------------------------- About the Master Program: Data Analytics Masters Program makes you proficient in tools and systems used by Data Analytics Professionals. It includes in-depth training on Statistics, Data Analytics with R, SAS, and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe. ------------------------------------- Prerequisites: There are no prerequisites for enrollment to the Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Data Analyst, Masters Program is designed and developed to accommodate various professional backgrounds ---------------------------------------- Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_lea... Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ------------------------------------- Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
Views: 12149 edureka!
Data Science In 5 Minutes | Data Science For Beginners | What Is Data Science? | Simplilearn
 
04:38
This Data Science tutorial video will give you an idea on the life of a Data Scientist, steps involved in Data science project, roles & salary offered to a Data Scientist. Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. Data Science is basically dealing with unstructured and structured data. Data Science is a field that comprises of everything that is related to data cleansing, preparation, and analysis. In simple terms, it is the umbrella of techniques used when trying to extract insights and information from data. Now, let us get started and understand what is Data Science all about. Below topics are explained in this Data Science tutorial: 1. Life of a Data Scientist 2. Steps in Data Science project - Understanding the business problem - Data acquisition - Data preparation - Exploratory data analysis - Data modeling - Visualization and communication - Deploy & maintenance 3. Roles offered to a Data Scientist 4. Salary of a Data Scientist To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Read the full article here: https://www.simplilearn.com/career-in-data-science-ultimate-guide-article?utm_campaign=What-is-Data-Science-bTTxei-S1WI&utm_medium=Tutorials&utm_source=youtube Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course. Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to: 1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics. Install the required Python environment and other auxiliary tools and libraries 2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions 3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave 4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package 5. Gain expertise in machine learning using the Scikit-Learn package The Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in analytics and data science 5. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=What-is-Data-Science-X3paOmcrTjQ&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simp... - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 372755 Simplilearn
Operator's Social Media Data Analysis (using MicroStrategy)
 
10:31
Welcome to Demo on Sentiment Analysis using Operator's Social Media Data Background & Purpose The purpose of the application is to analyze the customer sentiment (positive, neutral or negative) towards the services of two major Indian Operators -- Vodafone & Airtel. The application makes use of social media data of these Telco's for Analysis. Operators use social media platform as a promotional channel to increase awareness of their products and services and also, to address complaints of customers. Customer comes to these Facebook and Twitter pages to highlight any problems they are facing with the service. Since, social media posts have a high chance of going viral through re-post and re-tweets, hence a dedicated team is assigned to analyze all posts so as to resolve the customer complaints in a timely manner. The application would be of help to operators to do a comparative analysis of how their service is perceived by customer w.r.t to that of their competitors and draw actionable insights of the areas where they need to focus on. For example, geographical areas where they need to improve their network revise existing rate plans or offer new products. Data The data in the application is scrapped from Twitter and Facebook pages of Vodafone and Airtel. Analytical tool 'R' is then used to process this data to identify the sentiment of post/tweet and determine the category of the post such as Rate Plan, Billing, Network etc. Processed data is downloaded in form of an xls and used by MicroStartegy Analytic Desktop for Analysis (open xls attachments). Metrics like 'City' from where post was made, Number of followers, Page Rank of the posters are also captured. Analysis I shall now walk you through each of the dashboards(twitter, facebook) and describe the various visualizations. There are principally two dashboards in the application that provides ability to do analysis on Vodafone and Airtel social media by criteria such as - • Location • Influencer • Post Category I hope you have enjoyed Sentiment Analysis of Operator's Social media data. Thank you for taking time to watch this demo. Please also have a look at some of other demos as well.
Views: 1371 Rajat Mehta
R Tutorial For Beginners | R Programming Tutorial l R Language For Beginners | R Training | Edureka
 
01:33:00
( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R Tutorial (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R tool and help you build a strong foundation in R. Below are the topics covered in this tutorial: 1. Why do we need Analytics ? 2. What is Business Analytics ? 3. Why R ? 4. Variables in R 5. Data Operator 6. Data Types 7. Flow Control 8. Plotting a graph in R Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Telegram: https://t.me/edurekaupdates
Views: 542746 edureka!
Data Mining with Weka (1.6: Visualizing your data)
 
08:38
Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 6: Visualizing your data http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 72114 WekaMOOC
How to Clean Up Raw Data in Excel
 
10:54
Al Chen (https://twitter.com/bigal123) is an Excel aficionado. Watch as he shows you how to clean up raw data for processing in Excel. This is also a great resource for data visualization projects. Find the rest of the class here: https://skl.sh/31z4p1I Subscribe to Skillshare’s Youtube Channel: http://skl.sh/yt-subscribe Check out all of Skillshare’s classes: http://skl.sh/youtube Like Skillshare on Facebook: https://www.facebook.com/skillshare Follow Skillshare on Twitter: https://twitter.com/skillshare Follow Skillshare on Instagram: http://instagram.com/Skillshare
Views: 105968 Skillshare
Natural Language Processing In 10 Minutes | NLP Tutorial For Beginners | NLP Training | Edureka
 
08:26
** Natural Language Processing Using Python: https://www.edureka.co/python-natural-language-processing-course ** This Edureka video will provide you with a short and crisp description of NLP (Natural Language Processing) and Text Mining. You will also learn about the various applications of NLP in the industry. NLP Tutorial : https://www.youtube.com/watch?v=05ONoGfmKvA Subscribe to our channel to get video updates. Hit the subscribe button above. ------------------------------------------------------------------------------------------------------- #NLPin10minutes #NLPtutorial #NLPtraining #Edureka Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Instagram: https://www.instagram.com/edureka_learning/ ------------------------------------------------------------------------------------------------------- - - - - - - - - - - - - - - How it Works? 1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Natural Language Processing using Python Training focuses on step by step guide to NLP and Text Analytics with extensive hands-on using Python Programming Language. It has been packed up with a lot of real-life examples, where you can apply the learned content to use. Features such as Semantic Analysis, Text Processing, Sentiment Analytics and Machine Learning have been discussed. This course is for anyone who works with data and text– with good analytical background and little exposure to Python Programming Language. It is designed to help you understand the important concepts and techniques used in Natural Language Processing using Python Programming Language. You will be able to build your own machine learning model for text classification. Towards the end of the course, we will be discussing various practical use cases of NLP in python programming language to enhance your learning experience. -------------------------- Who Should go for this course ? Edureka’s NLP Training is a good fit for the below professionals: From a college student having exposure to programming to a technical architect/lead in an organisation Developers aspiring to be a ‘Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Text Mining Techniques 'Python' professionals who want to design automatic predictive models on text data "This is apt for everyone” --------------------------------- Why Learn Natural Language Processing or NLP? Natural Language Processing (or Text Analytics/Text Mining) applies analytic tools to learn from collections of text data, like social media, books, newspapers, emails, etc. The goal can be considered to be similar to humans learning by reading such material. However, using automated algorithms we can learn from massive amounts of text, very much more than a human can. It is bringing a new revolution by giving rise to chatbots and virtual assistants to help one system address queries of millions of users. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Human language, developed over thousands and thousands of years, has become a nuanced form of communication that carries a wealth of information that often transcends the words alone. NLP will become an important technology in bridging the gap between human communication and digital data. --------------------------------- For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free).
Views: 68653 edureka!
Introduction to text mining with Voyant
 
23:48
In this introduction to text mining with Voyant I cover: 1) Data cleaning (text editors, Notepad++ and Sublime Text) 2) Loading your text into Voyant 3) Expectations, what Voyant can and cannot do 4) Working with common visualization tools and making possible connections 5) Exporting visualizations
Twitter Sentiment analysis with SAP® HANA® and SAPUI5 Part - 1(2018)
 
01:15:05
Git code: https://github.com/manasvi2001/Twitter-Sentiment-Analysis Running App: http://hana.skybuffer.com/workshop/sessiona/00/ui/kpitiles/WebContent/index.html Twitter Developer Console: https://apps.twitter.com/ SkyBuffer: https://www.skybuffer.com/ Content: 00:00 It starts 00:23 About the webinar 01:01 Why Sentiment Analysis is important 02:52 How to get data from twitter 03:43 Intro to SAP® HANA® 04:35 Background of Semtiment Analysis 06:16 Tweet hashtag focus in this webinar 06:57 Architecture of the app 07:00 Python Scripting 9:10 Get your own API keys 10:00 Script Walkthrough 10:34 Twython library 12:50 Use python 2.7 for this script 14:14 How do we do sentiment analysis here 18:20 Basics of HANA® Development Environment 19:22 Downloading HANA® tools for eclipse 24:10 Creating a workspace 21:14 Adding HANA® system 21:57 Free trial access to HANA® system 27:20 Manasvi trying to create a new project in system :P 27:33 Adding a new project to local machine 32:46 Sharing project to remote server 35:02 A look at tweets retrieved 36:54 Application Descriptors 39:54 Creation of Tables 40:49 Structure of HANA® Tables 43:08 Schema 50:34 Loading data to Tables 54:44 Error while loading data 55:56 SQL console in eclipse HANA® development studio 58:18 Success loading data 59:31 Seeing data preview 01:00:6 Creating positive table 01:02:27 Creating negative table 01:07:39 Test using SQL queries on SQL console 01:13:54 About SkyBuffer 01:14:47 See you next week As business enterprises increase their social media footprint, their organizational success is fast being decided by the effectiveness of their social engagement strategies. You have to be spot-on in knowing what your customers’ likes, dislikes, wants and needs are. Twitter in that regards is one of the best platforms to know your customer's sentiment. So your decisions are better when it matters. .
Data Science Dojo Alumni - Mohamed Kashkoush
 
01:25
Before coming to the Toronto 2018 Data Science Dojo bootcamp, Mohamed Kashkoush already had solid background in mathematics and statistics, as well as experience with data mining, but wanted to catch up with the newest tools and technologies that are being offered in the data science industry. Unable to take much time away from his career, Mohamed found that the five-day bootcamp was the perfect for him, and was especially impressed by the bootcamp's balance between data science theory and practice. He found the classroom environment to be very beneficial to his learning experience, and appreciated the collaborative nature of the camp. -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 3600+ employees from over 742 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0fBgSQ0 See what our past attendees are saying here: https://hubs.ly/H0fBgSZ0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 117 Data Science Dojo
Analyzing Big Data with Twitter - Lecture 1 - Intro to course; Twitter basics
 
51:23
http://blogs.ischool.berkeley.edu/i290-abdt-s12/ Course: Information 290. Analyzing Big Data with Twitter School of Information UC Berkeley Lecture 1: August 23, 2012 Course description: How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered. This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.
Data Mining with Weka (1.3: Exploring datasets)
 
10:38
Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 3: Exploring datasets http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 83719 WekaMOOC
Parameters and Templates with Power BI Desktop
 
10:52
In this video, Patrick shows a way you can use parameters and templates, with Power BI Desktop, to provide prompts for your connection's server and database properties. This is great for when you are creating a report, and need to share it with a customer that may have a different name for the server and database name, but the database schema is the same. LET'S CONNECT! Guy in a Cube -- https://guyinacube.com -- http://twitter.com/guyinacube -- http://www.facebook.com/guyinacube -- Snapchat - guyinacube -- https://www.instagram.com/guyinacube/ ***Gear*** Check out my Tools page - https://guyinacube.com/tools/
Views: 39652 Guy in a Cube
PART 11 | ADOBE PHOTOSHOP 7.0 IN HINDI | PHOTOSHOP 7.0 TUTORIALS HINDI | फोटोशॉप टूल्स | HINDI URDU
 
13:15
ADOBE PHOTOSHOP 7.0 IN HINDI BASIC TOOLS TUTORIAL Hello Wel-come to studio gulshan art dosto, is vedio mai aap dekhenge adobe photoshop 7.0 tutorial basic tools ki puri jankari hindi mai puri duniya mai photo edite karne ke liye sabse jyada use adobe photoshop 7.0 ka hi hota hai isliye hamne adobe photoshop 7.0 tools tutorial banakar apko bataane ki koshish ki hai aapko hamaare samjhane ka tarika kesa lagaa hame jarur bataye taaki ham adobe photoshop 7.0 ke tutorial pure hone ke baad adobe photoshop cc adobe photoshop cs3 adobe photoshop cs6,adobe photoshop cc_2019 or light room ke vedio tutorial bhi apko banakar bataa sake about vedio filhaal is vedio mai hamne aapko adobe photoshop 7.0 ka basic bataya hai jese adobe photoshop 7.0 me blur ka upyog kis tarah se kiya jata hai adobe photoshop 7.0 me sharpen tools ka upyog kis tarah se kiya jata hai adobe photoshop 7.0 me smudge tools ka upyog kis tarah se kiya jata hai about channel agar aapko hamari vedio achchi lagti hai to hamare channel ko aage badane mai hamara support kijiye hamare channel per apko ADOBE PHOTOSHOP ADOBE PHOTOSHOP CC portable ADOBE PHOTOSHOP CS2 ADOBE PHOTOSHOP CS3 ADOBE PHOTOSHOP CS6 ADOBE PHOTOSHOP CC_2019 or lightroom KI PURI JANAKARI HINDI OR URDU ME DI JATI HAI so keep watching and support my youtube channels agar aapko photoshop se sambandhit koi bhi problem s ho to aap be jhijhak hamse comment me puch sakte hai thanks वेलकम-टू स्टूडियो गुलशन आर्ट दोस्तो इस वीडियो में आप देखेंगे एडोब फोटोशॉप 7.0 ट्यूटोरियल बेसिक टूल्स की पुरी जानकारी हिंदी में पूरी दुनिया में फोटो को एडिट करने के लिए एडोबी फोटोशॉप का उपयोग सबसे ज्यादा होता हे इसीलिए हमने एडोब फोटोशॉप 7.0 ट्यूटोरियल बनाकर आपको बताने की कोशिश की है आपको हमारे समझाने का तरीका कैसा जरूर बताएं ताकि हम आगे से एडोबी फोटोशॉप 7.0 के टूटोरियल पुरे होने के बाद एडोबी फोटोशॉप सीसी , एडोबी फोटोशॉप cs2 एडोबी फोटोशॉप cs3 एडोबी फोटोशॉप cs6 एडोबी फोटोशॉप cc_2019 और लाइट रूम के वीडियो टूटोरियल भी बनाकर आपको बता सके अगर आपको हमारी वीडियो अच्छी लगती हे तो हमारे चैनल को आग बढ़ाने में हमारी मदद कीजिये हमारे चेंनेल पर आपको एडोबी फोटोशॉप बेसिक टूल्स टुटोरियल एडोबी फोटोशॉप 7.0 एडोबी फोटोशॉप cs2 एडोबी फोटोशॉप cs3 एडोबी फोटोशॉप cc एडोबी फोटोशॉप cs6 एडोबी फोटोशॉप cc एडोबी फोटोशॉप cc_2019 लाइट रूम आदि की जानकरी पूरी तरह से हिंदी और उर्दू भाषा मिलेगी धन्यवाद my social activity facebook page [ फेसबुक पेज ] - https://www.facebook.com/Studio-Gulshan-Art-148875648645392/ twitter [ ट्विटर ]- https://twitter.com/GafeelDashpuri instagram [इंस्टाग्राम ]- https://www.instagram.com/Gafil_Dashpuri/ other shayari youtube channel [अन्य शायरी यूट्यूब चैनल ]- https://www.youtube.com/c/gafildashpuri website [वेबसाइट ]- https://www.studiogulshan.com/ #studiogulshanart
Views: 94 STUDIO GULSHAN ART
5 Steps to Simple Data Visualization for Nonprofits
 
03:38
Data visualization is an effective way to communicate your nonprofits impact because humans are able to process images 60,000x faster than we can process text. Thus, images are a powerful tool while conveying your nonprofits message. You will learn: -how to make data visualizations on Google Sheets -how to choose the right type of graph -how to customize and organize a more effective visualization -how to embed and use this interactive data viz We know that it is not always the most accessible thing to for non-coders, but luckily, we have found a simple way for data viz using Google Sheets, which makes it extremely simple, accessible, and easy to update. 1. Use the right type of graph (01:03) What’s your goal with the viz? Is it to highlight relationships or to show composition? Nailing down these questions will help you decide on which graph to use. Here are the options on Google Sheets, and how we would recommend using them: Gauge chart: show goal and progress Map: show breadth of your programs Motion chart: emphasize progress/growth over time 2. Organize and clean (01:39) After choosing your graph type, Google Sheets will generate that chart for you, but all its features may not be relevant in your situation. Some questions that you may want to ask during this stage include: Are background lines necessary? Does the sorting order make sense? Remove or sort things more clearly to match your needs after answering these questions. 3. Format labels and legends (02:09) The next step is to go in even closer and edit the labels and legends so that people can better understand what exactly the chart is showing. This is the stage that you should: Add title and name of axis Remove legend if necessary 4. Customize design (02:22) Although Google Sheets does not have the best tools to manipulate the colors since there is not a custom option, you can get pretty close by trying to match your colors to the palette provided. 5. Publish and embed (02:43) Now just publish this graph on Google Sheets. Once you've done that, you can copy the embed code and paste it onto your site. Embedding the interactive graph is the same process as embedding a Youtube video, so it's You can assemble these graphs together and tie them with a narrative to show the impact that your nonprofit has made. Get out there are start making some awesome graphs to show off your great work! ------- Whole Whale is a digital agency that leverages data and technology to increase the impact of nonprofits. In the same way the Inuits used every part of whale, Whole Whale leverages existing resources to see, "What else can this do for us?" By using data analysis, digital strategy, web development, and training, WW builds a 'Data Culture' within every nonprofit organization they work with. ------- Check us out on Facebook : https://www.facebook.com/WholeWhale Tweet us: https://twitter.com/WholeWhale Visit our website: http://wholewhale.com/
Views: 2740 WholeWhale
MSBI Tutorials for Beginners | Business Intelligence Tutorial | Learn MSBI | MSBI Training | Edureka
 
01:22:15
This Edureka MSBI Tutorial video will help you learn the basics of MSBI. This powerful suite is composed of tools which helps in providing best solutions for Business Intelligence and Data Mining Queries.This video will help you master MSBI concepts such as SSIS, SSAS and SSRS along with demo using SQL Server and Data Tools. Below are the topics covered in this tutorial: 1. Why Business Intelligence? 2. What is BI? 3. BI tools 4. Why Microsoft BI? 5. What is Microsoft BI? 6. Microsoft BI Architecture 7. Tools & Utilities of Microsoft BI 8. Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Microsoft BI playlist here: https://goo.gl/Vo6Klo #MicrosoftBI #MicrosoftBItutorial #MicrosoftBIcourse How it Works? 1. This is a 30 Hours of Online Live Instructor-Led Classes. Weekend Class : 10 sessions of 3 hours each. Weekday Class : 15 sessions of 2 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! --------------------------------------------------- About the Course Edureka's Microsoft BI Certification Course is designed to provide insights on different tools in Microsoft BI Suite (SQL Server Integration Services, SQL Server Analysis Services, SQL Server Reporting Services). Get expertise in SSIS , SSAS & SSRS concepts and master them. The course will give you the practical knowledge on Data Warehouse concepts and how these tools help in developing a robust end-to-end BI solution using the Microsoft BI Suite. --------------------------------------------------- Who should go for this course? Microsoft BI Certification Course at Edureka is designed for professionals aspiring to make a career in Business Intelligence. Software or Analytics professionals having background/experience of any RDBMS, ETL, OLAP or reporting tools are the key beneficiaries of this MSBI course. You can check a blog related to Microsoft BI – Why You Need It For A Better Business Intelligence Career!! Also, once your Microsoft BI training is over, you can check the Microsoft Business Intelligence Interview Questions related edureka blog. --------------------------------------------------- Why learn Microsoft BI ? As we move from experience and intuition based decision making to actual decision making, it is increasingly important to capture data and store it in a way that allows us to make smarter decisions. This is where Data warehouse/Business Intelligence comes into picture. There is a huge demand for Business Intelligence professionals and this course acts as a foundation which opens the door to a variety of opportunities in Business Intelligence space. Though there are many vendors providing BI tools, very few of them provide end to end BI suite and huge customer base. Microsoft stands as leader with its user-friendly and cost effective Business Intelligence suite helping customers to get a 360 degree view of their businesses. Please write back to us at [email protected]co or call us at +918880862004 or 18002759730 for more information. Website: https://www.edureka.co/microsoft-bi Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Amit Vij, HRSSC HRIS Senior Advisor at DLA Piper, says "I am not a big fan of online courses and also opted for class room based training sessions in past. Out of surprise, I had a WoW factor when I attended first session of my MSBI course with Edureka. Presentation - Check, Faculty - Check, Voice Clarity - Check, Course Content - Check, Course Schedule and Breaks - Check, Revisting Past Modules - Awesome with a big check. I like the way classes were organised and faculty was far above beyond expectations. I will recommend Edureka to everyone and will personally revisit them for my future learnings."
Views: 47192 edureka!
What is SSIS , SSAS and SSRS ( part 1)  with sample demo?
 
11:13
For more such videos visit http://www.questpond.com See our other Step by Step video series below :- Learn angular tutorial for beginners https://tinyurl.com/ycd9j895 Learn MVC Core step by step :- http://tinyurl.com/y9jt3wkv Learn MVC 5 Step by Step in 16 hours:- https://goo.gl/dmdakg Learn MSBI Step by Step in 32 hours:- https://goo.gl/TTpFZN Learn Xamarin Mobile Programming Step by Step :- https://goo.gl/WDVFuy Learn Design Pattern Step by Step in 8 hours:- https://goo.gl/eJdn0m Learn C# Step by Step in 100 hours :- https://goo.gl/FNlqn3 Learn Data structures & algorithm in 8 hours :-https://tinyurl.com/ybx29c5s Learn SQL Server Step by Step in 16 hours:- http://tinyurl.com/ja4zmwu Learn Javascript in 2 hours :- http://tinyurl.com/zkljbdl Learn SharePoint Step by Step in 8 hours:- https://goo.gl/XQKHeP Learn TypeScript in 45 Minutes :- https://goo.gl/oRkawI Learn webpack in 50 minutes:- https://goo.gl/ab7VJi Learn Visual Studio code in 10 steps for beginners:- https://tinyurl.com/lwgv8r8 Learn Tableau step by step :- https://tinyurl.com/kh6ojyo =============================================== Learn MSBI in 4 days with Project ============================ Lab 1 :- MSBI Fundamentals, Data flow, Control Flow, ETL, Dataware house. (SSIS) :- https://youtu.be/mGPJx3ocFgg Lab 2:- Conditional split, Data conversion and Error handling. (SSIS) Lab 3:- For Loop, Variables, Parameters and Debugging. (SSIS) Lab 4:- Packaging and Deployment, File component and running SSIS package as a task.(SSIS) Lab 5: - For dimension, measures, star schema, snow flake, shared connection managers & packages tasks.(SSIS) Lab 6:- SCD, Type 0, Type 1, OLEDB Command and Unicode conversions.(SSIS) Lab 7:- Lookup, Data conversion optimization and updating SSIS package.(SSIS) Lab 8:- Sort, Merge and Merge Joins.(SSIS) Lab 9 :- Creating SSAS Cube. (SSAS) Lab 10:- SSAS Time series and Excel display.(SSAS) Lab11: - What are Transactions and CheckPoints in SSIS? (SSIS) Lab12: - Simple SSRS report & implementing Matrix, Tabular, Parameters, Sorting, Expressions. (SSRS) Lab 13:- Using Data Profiling task to check data quality. (SSIS) Lab 14:- Hierarchical Dimensions. (SSAS) Lab 15:- WebServices and XML Task. (SSIS) Lab16:- DrillDown and Subreports. (SSRS) Lab17 :- SSAS KPI (Key Performance Indicators). (SSAS) Lab 18:- Pivot, UnPivot and Aggregation. (SSIS) Lab 19 :- SSAS Calculation.(SSAS) Lab 20:- SQL Execute Task. (SSIS) Lab 21:- Reference and Many-to-Many Relationship. (SSAS) Lab 22 :- Script Task and Send Mail Task. (SSIS) Lab 23 :- Script component(SSIS) Lab 24 :- Bar chart, Gauge and Indicators.(SSRS) Lab 25:- Partitions in SSAS. (SSAS) Lab 26 :- CDC(Changed Data Capture) in SSIS. (SSIS) Lab 27:- Additive, Semiadditive and non-additive measures in SSAS.(SSAS) Lab 28:- Buffer Size Tuning (SSIS) Lab 29 :- How to implement Multithreading in SSIS?(SSIS) Lab 30:- Processing SSAS cube in background.(SSAS) Lab 31 :- Explain Asynchronous, Synchronous, Full, Semi and Non blocking Components. (SSIS) Lab 32 :- SSRS Architecture and Deployment (SSRS) Lab 33 :- DQS( Data Quality Services ) (SSIS) Lab 34 :- Explain Tabular Model and Power Pivot (SSAS). Lab 35 :- MDX (Multidimensional Expressions) Queries.(SSAS) Lab 36 :- Data Mining (Fundamentals and Time Series Algorithm).(SSAS) Lab 37 :- Page Split and Performance issues with SSIS.(SSIS) Lab 38 :- Aggregations in SSAS.(SSAS) Lab 39 :- ROLAP, MOLAP and HOLAP.(SSAS) Lab 40 :- Instrumentation using Data Taps (SSIS). Lab 41:- Lookup caching modes and Cache Transform. (SSAS) Lab 42: - Perspectives & Translations. (SSAS) Lab 43 :- Tabular Training 1 :- Installation, Xvelocity, Vertipaq, DAX,Creating cubes,measures, KPI, Partition and Translation? In this video we will try to understand what is SSIS , SSRS and SSAS, We also see a sample demo of ETL ( Extraction transformation and loading). This video series is for people who wants to Microsoft business intelligence. We are also distributing a 200 page Ebook "Learn MSBI (SSIS, SSRS, SSAS) Step by step". If you want this ebook please share this video in your facebook/twitter/linkedin account and email us on [email protected] with the shared link and we will email you the PDF. Buy Questpond videos on discount - http://www.itfunda.com/Interview
Blockchain Tutorial For Beginners - 1 | Blockchain Technology | Blockchain Tutorial | Simplilearn
 
29:19
This Blockchain tutorial video will help you understand what is Blockchain, the Bitcoin story, features of Blockchain which includes public distributed ledger, hash encryption, proof of work, mining and at the end you will also see a use case on how banks are using Blockchain in validating user identities. A blockchain is a digitized, decentralized, public ledger of Bitcoin transactions. The technology verifies transactions and creates a “chain” of blocks of data including a timestamp that is linked to other blocks so that a block can’t be changed. In simple words, Blockchain is a list of records (blocks) which stores data publicly and in chronological order and mining is the process of adding a block to the Blockchain. Now, let us get started and understand what is Blockchain and its features. Below topics are explained in this Blockchain tutorial: 1. What is Blockchain? ( 03:07 ) 2. The Bitcoin story ( 04:43 ) 3. Features of Blockchain ( 06:48 ) - Public distributed ledger - Hash encryption - Proof of work - Mining 4. Use case: Blockchain and banks ( 19:48 ) Blockchain Tutorial Part - 2 : https://www.youtube.com/watch?v=ov8nVP6dowc Click the below link to get the code implemented in the demo: https://github.com/pjai30/KYC To learn more about Blockchain, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the Slides here: https://goo.gl/J2vNsh Watch more videos on Blockchain: https://www.youtube.com/playlist?list=PLEiEAq2VkUUKmhU6SO2P73pTdMZnHOsDB #Whatisblockchain #Blockchain #Blockchaintutorial #Bitcoin #Blockchainonlinetraining #Blockchainforbeginners #BlockchainTechnology #Simplilearn Simplilearn’s Blockchain Certification Training has been designed for developers who want to decipher the global craze surrounding Blockchain, Bitcoin and cryptocurrencies. You’ll learn the core structure and technical mechanisms of Bitcoin, Ethereum, Hyperledger and Multichain Blockchain platforms, use the latest tools to build Blockchain applications, set up your own private Blockchain, deploy smart contracts on Ethereum and gain practical experience with real-world projects. Why learn Blockchain? Blockchain technology is the brainchild of Satoshi Nakamoto, which enables digital information to be distributed. A network of computing nodes makes up the Blockchain. Durability, robustness, success rate, transparency, incorruptibility are some of the enticing characteristics of Blockchain. By design, Blockchain is a decentralized technology which is used by a global network of the computer to manage Bitcoin transactions easily. Many new business applications will result in the usage of Blockchain such as Crowdfunding, smart contracts, supply chain auditing, etc. This Blockchain Certification course offers a hands-on training covering relevant topics in cryptocurrency and the wider Blockchain space. From a technological standpoint, you will develop a strong grasp of core Blockchain platforms, understand what Bitcoin is and how it works, learn key vocabulary and concepts commonly used when discussing Blockchain and understand why engineers are motivated to create an app with Ethereum. After completing this course, you will be able to: 1. Apply Bitcoin and Blockchain concepts in business situations 2. Build compelling Blockchain applications using the Ethereum Blockchain 3. Design, test and deploy secure Smart Contracts 4. Use the latest version of Ethereum development tools (Web3 v1.0) 5. Develop Hyperledger Blockchain applications using Composer Framework 6. Model the Blockchain applications using Composer modeling language 7. Develop front-end (client) applications using Composer API 8. Leverage Composer REST Server to design a web-based Blockchain solution 9. Design Hyperledger Fabric Composer Business Network 10. 10. Understand the true purpose and capabilities of Ethereum and Solidity The Blockchain Certification Training Course is recommended for: 1. Developers 2. Technologists interested in learning Ethereum, Hyperledger and Blockchain 3. Technology architects wanting to expand their skills to Blockchain technology 4. Professionals curious to learn how Blockchain technology can change the way we do business 5. Entrepreneurs with technology background interested in realizing their business ideas on the Blockchain Learn more at: https://www.simplilearn.com/blockchain-certification-training?utm_campaign=Blockchain-Tutorial-Part-1-iYYf3w4RPDA&utm_medium=Tutorials&utm_source=youtube For more updates on courses and tips follow us on: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 15774 Simplilearn
How Do You Track Your Twitter Statistics?
 
06:18
http://geeks.pirillo.com - http://live.pirillo.com - Literally millions of people belong to this social commons known as Twitter. The best part of Twitter is being able to learn about people I would otherwise never have known. Tracking your statistics on Twitter isn't always easy, but thankfully there's a new way to do so. http://chris.pirillo.com Distributed by Tubemogul.
Views: 10164 Chris Pirillo
Deep Dive into Machine Learning in ArcGIS Platform
 
04:25:32
In this hands-on workshop, you will be exposed to machine learning in the ArcGIS Platform (Pro and Online), in addition to Python integration to leverage powerful machine learning and deep learning libraries. You will learn advanced use patterns and best practices for machine learning tools in ArcGIS Pro, in addition to best practices for integrating external machine learning libraries. After this workshop you will be equipped with: - Workflows for setting up a machine learning environment in your computer - Ability to create complex, predictive GIS workflows powered by statistical machine learning tools - Experience to work with spatial and spatio-temporal data in the context of machine learning - Use cases and datasets to adapt for your own analysis - Advanced patterns for integrating deep learning in ArcGIS Pro Participants are expected to bring their own laptops, have admin rights to their machines and have ArcGIS Pro installed on their machines. -------------------------------------------------------------------------------------------------------------------------- Follow us on Social Media! Twitter: https://twitter.com/Esri Facebook: https://facebook.com/EsriGIS LinkedIn: https://www.linkedin.com/company/esri Instagram: https://www.instagram.com/esrigram The Science of Where: http://www.esri.com
Views: 631 Esri Events
Visualizing Twitter + Bing + Google Trends + Demographics for Pepsico Brands
 
02:32
This is an example that I put together to visualize and correlate Demographic Data (Median Income) with Twitter activity, Bing Search Trends, Google Trends using Excel 2013. The Data was acquired using Power Query for Excel. The relationships between the diverse data sets was established using PowerPivot and the visualizations built using Power View & Power Map for Excel
Views: 1328 ShiSh S
Data Mining with Weka (1.1: Introduction)
 
09:00
Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 1: Introduction http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 130410 WekaMOOC
DEF CON 20 - Chris "TheSuggmeister" Sumner and Randall Wald - Can Twitter Expose Psychopath Killers?
 
48:29
Copy of the slides for this talk are here:https://media.defcon.org/dc-20/presentations/Sumner/DEFCON-20-Sumner-Can-Twitter-Help-Expose-Psychopath-Killers-Traits.pdf Can Twitter Really Help Expose Psychopath Killers' Traits? Chris "TheSuggmeister" Sumner The Online Privacy Foundation Randall Wald Recent research has identified links between Psychopaths and the language they use (Hancock et al 2011), with media reports suggesting that such knowledge could be applied to social networks in order help Law Enforcement Agencies expose "Psychopath killers' traits". This is the first public study to research Psychopathy in the context of social media. This study explored the extent to which it is possible to determine Psychopathy, and other personality traits based on Twitter usage. This was performed by comparing self-assessment 'Dark Triad' (Psychopathy, Machiavellianism, Narcissism) and 'Big Five' (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism) personality traits with the Twitter information, usage and language of 2927 participants. Results show that there are a number of statistically significant correlations between an individual's darker personality traits and their Twitter activity. We also identified links between users' attitudes to privacy, their personality traits and their twitter use. We will present the improvement gains possible through the use of machine learning for personality prediction and share the models and techniques employed. In addition to presenting our results, this talk will provide an introduction into identifying psychopathic traits using the Hare Psychopathy Checklist (PCL-R), present the technical approaches to collecting, storing and analyzing Twitter data using Open Source technologies and discuss the current ethical, privacy and human rights concerns surrounding social media analysis, vetting and labeling. We will conclude with two proof of concept works, the first using the visualization tool Maltego to explore how visual analysis could be used to identify potential troublemakers at events such a far right demonstrations; the second to look at how personality traits influence response and interaction with a benign Twitter Bot. The results highlight that in certain contexts, personality prediction through social media can perform with a reasonably high degree of accuracy. Chris is a contributor in the emerging discipline of Social Media Behavioral Residue research where he combines his interests in Psychology, Social Networks, Data Mining and Visual Analytics. He has previously spoken about these topics at BlackHat and DEF CON and is scheduled to speak at the European Conference on Personality in July 2012 with a team of academic personality researchers. Chris has been directly involved in Corporate Information Security at Hewlett-Packard since 1999 and is currently focused on Security in the Development Lifecycle. Outside of work and together with a small group of likeminded individuals, he co-founded the not-for-profit Online Privacy Foundation to conduct topical research and raise security awareness at a community level. Twitter: @TheSuggmeister https://www.facebook.com/onlineprivacyfoundation http://www.onlineprivacyfoundation.org/ Randall Wald is a researcher studying data mining and machine learning at Florida Atlantic University. Following his BS in Biology from the California Institute of Technology, Randall chose to shift his focus to computer science, applying his domain knowledge towards bioinformatics and building models to predict disease. He also studies machine learning for other domains, including machine condition monitoring, software engineering, and social networking. http://www.ceecs.fau.edu/directory/randallwald
Views: 365 DEFCONConference
Channel Update - May 2019
 
01:44
We wanted to let you know that we are dropping down to two videos a week, from four. We will be releasing two videos a week for about the next two months. Monday will be the roundup and Wednesday will be the tech video from either Patrick or Adam. This is to free up bandwidth to work on some awesome projects we have in mind. ******** LET'S CONNECT! ******** -- http://twitter.com/guyinacube -- http://twitter.com/awsaxton -- http://twitter.com/patrickdba -- http://www.facebook.com/guyinacube -- https://www.instagram.com/guyinacube/ -- https://guyinacube.com ***Gear*** Check out my Tools page - https://guyinacube.com/tools/
Views: 2922 Guy in a Cube
RStudio Tutorial For Beginners | RStudio Installation  | R Tutorial | R Training | Edureka
 
24:02
( R Training : https://www.edureka.co/r-for-analytics ) This Edureka RStudio Tutorial For Beginners will help you in understanding the need for Rstudio and how it is used. Check out our blog: R Tutorial – A Beginner’s Guide to Learning R Programming( https://goo.gl/UeKg5g ) Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #RStudio #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 57584 edureka!
Creating, Content, The Data Mine And Convincing Kelvin To Change A Background
 
50:28
► Subscribe to EAP's Channel Here - http://bit.ly/EasyAgentProSubscribe EAP'S NEW DASHBOARD IS OUT! And it's awesome. See more here: https://www.youtube.com/watch?v=XnBp6Czfllo Beat Zillow Questions: https://facebook.com/groups/leadsites/ Gene Petrino‎ - I am going to start to interview some local businesses and try to get backlinks on their sites. My question is, does EAPer have experience with this? How long should the interview be, and what are some good questions I should be asking? Thanks in advance. Awesome Article On Backlinks: http://backlinko.com/on-page-seo Rebekah Foster - I think many of us are struggling to test squeeze pages. Video on how to split test landing pages: https://www.youtube.com/watch?v=al9lbKLND9U Cory Fast - I recently ran an ad to a list of foreclosures and built an audience based on just the Interest section (real estate related interest and 10 mile radius of office) and had 5 leads with ad spend of $35. Thought I would get smart and use a lookalike audience from an email list of 240 leads from 2016 (also 10 mile radius) Ran same ad creative and copy with just one lead in $49 spent. Both for a week. So the first with jutst Interest Section performed better. So the question, is a lookalike audience really better than just using the Interest section? And then the other element to compare would be if a lookalike audience of all the following on a specific Facebook page would do better or worse than either. And a little further, is it worth the energy to build a following or better to just tie into Facebook's huge data mine? Karin Atkinson Carr - Researching SEO keywords. I find the Google keyword planner to be really UNhelpful for choosing specific niches. I want to rank for a new development in my area and I come up with zero results for Oakhaven, so how do I choose a keyword when Google tells me there are 0 searches a month being done for that neighborhood? Leopeter Alvarez - When detail targeting on Facebook Ads... Is there a such thing as targeting too many interests, demographics etc? (If you live in a city where audiences are still generally large) Shreedhar Ganapathy - While I have your attention, I have a request. Perhaps you could cover this in a future episode or blog. How does a Realtor earn that initial trust with a completely new non-referral prospect from a different culture (seller or buyer)? Particularly, in the case of people from other cultures such as Asian cultures as an example (it sort of applies to many other cultures as well in that what is recommended generally as a feasible approach, may not apply to others). The cultural aspect has a major impact on business prospects. Its tough to tell what sort of verbiage may win the confidence of the prospect and convince them of your high integrity, ability and skills. My wife is a Realtor and frequently comes across this challenge almost like a wall that prevents further progress. Would appreciate any tips. #LINKS: EAP Tips: https://www.easyagentpro.com/blog Facebook: https://www.facebook.com/easyagentpro/ Twitter: https://twitter.com/easyagentpro Instagram: https://www.instagram.com/easyagentpro/ More Videos: -- Easy Agent Pro helps real estate agents grow their business. They've been featured on Inman, RIS Media, RESAAS, and more. You can find new marketing tips, tricks, tactics and strategies at EasyAgentPro. #EAPTV is one source of real estate marketing tips for real estate agents. Tyler Zey focused on providing as much value as possible by talking about social media, websites, lead generation, lead conversion, and business. Easy Agent Pro is the maker of LeadSites ► http://bit.ly/LeadSites These are real estate websites that provide the best tools and apps for agents to generate leads in a modern, digital world. Check them out today.
Views: 236 Easy Agent Pro
Lecture 12 -Analyzing Big Data with Twitter: Recommender Systems by Alpa Jain
 
01:15:05
http://blogs.ischool.berkeley.edu/i290-abdt-s12/ Alpa Jain on Recommender Systems Course: Information 290. Analyzing Big Data with Twitter School of Information UC Berkeley Prof. Marti Hearst Course description: How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered. This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.
Data Mining with Weka (1.5: Using a filter )
 
07:34
Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 5: Using a filter http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/IGzlrn https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 71803 WekaMOOC
Oil Drilling | Oil & Gas Animations
 
08:22
- Like our Facebook: https://www.facebook.com/oilvips - Geologists and geophysicists have agreed on the existence of a "prospect", a potential field. In order to find out if hydrocarbons are indeed trapped in the reservoir rock, we must drill to hit them. Bearing in mind the knowledge acquired about the substratum and the topography of the land, the best position for the installation of the drilling equipment is determined. Generally it is vertically above the point of maximum thickness of the geological layer suspected of containing hydrocarbons. The drillers then make a hole in conditions that are sometimes difficult. Of small diameter (from 20 to 50 cm) this hole will generally go down to a depth of between 2000 and 4000 meters. Exceptionally, certain wells exceed 6000 m. One of them has even exceeded 11 000 m! Certain fields can be buried at a depth equivalent to the height of 12 Eiffel Towers ... The derrick is the visible part of the drilling rig. It is a metal tower several tens of meters high. It is used to vertically introduce the drill strings down the hole. These drill strings are made up of metallic tubes screwed end to end. They transmit a rotating movement (rotary drilling) to the drilling tool (the drill bit) and help circulate a liquid called "mud" (because of its appearance) down to the bottom of the well. The drilling rig works like an enormous electric hand-drill of which the derrick would be the body, the drill strings the drive and the drilling tool the drill bit. The most usual tool is an assembly of three cones -- from which comes the name "tri cone" -- in very hard steel, which crushes the rock. Sometimes when the rock being drilled is very resistant, a single- block tool encrusted with diamonds is used. This wears down the rock by abrasion. Through the drill pipes, at the extremity of which the drill bit rotates, a special mud is injected, which the mud engineer prepares and controls. This mud cools the drill bit and consolidates the sides of the borehole. Moreover it avoids a gushing of oil, gas or water from the layer being drilled, by equilibrating the pressure. Finally, the mud cleans the bottom of the well. As it makes its way along the pipes, it carries the rock fragments (cuttings) to the surface. The geologist examines these cuttings to discover the characteristics of the rocks being drilled and to detect eventual shows of hydrocarbons. The cuttings, fragments of rock crushed by the drill bit, are brought back up to the surface by the mud. To obtain information on the characteristics of the rock being drilled, a core sample is taken. The drill bit is replaced by a hollow tool called a core sampler, which extracts a cylindrical sample of several meters of rock. This core supplies data on the nature of the rock, the inclination of the layers, the structure, permeability, porosity, fluid content and the fossils present. After having drilled a few hundred of meters, the explorers and drillers undertake measurements down the hole called loggings, by lowering electronic tools into the well to measure the physical parameters of the rock being drilled. These measures validate, or invalidate, or make more precise the hypotheses put forward earlier about the rocks and the fluids that they contain. The log engineer is responsible for the analysis of the results of the various loggings. The sides of the well are then reinforced by steel tubes screwed end to end. These tubes (called casings) are cemented into the ground. They isolate the various layers encountered. When hydrocarbons are found, and if the pressure is sufficient to allow them come to the surface naturally, the drillers do a flow check. The oil is allowed to come to the surface during several hours or several days through a calibrated hole. The quantity recovered is measured, as are the changes in pressure at the bottom of the well. In this way, a little more knowledge is gained about the probable productivity of the field. If the field seems promising, the exploration team ends the first discovery well and goes on to drill a second, even several others, several hundred or thousand meters further away. In this way, the exploration team is able to refine its knowledge about the characteristics of the field. The decision to stop drilling is made only when all these appraisal wells have provided sufficient information either to give up the exploration or to envisage future production. --------------------------------------------------------------------------------------- Like our Facebook: https://www.facebook.com/oilvips Twitter: https://twitter.com/oilvips And Don't forget to subscribe to our channel
Views: 808167 Oil & Gas Videos
Power BI Custom Visual using R and JSON
 
56:12
Power BI visualization is a holistic visualization tool. You can draw most of the popular charts with it. However, there is always some needs for specific charts that may not be available in Power BI standard visualizations of the marketplace. There is a possibility to extend the visualization capabilities using R language. There are two ways to use R to extend the visualization possibilities. The approach was introduced in 2015 as “R” custom visual that you can draw chart by writing R scripts. Drawing chart by writing R codes inside Power BI is so easy. However, the editor for writing R was not that was good and also the end-user able to see the R code behind the chart. The second approach for using R to have more chart in Power BI has been introduced in mid of 2017 that is about creating Custom visual file (pbiviz file) using R and JASON language. In this seminar, I am going to show how you can create any custom visual by writing R codes. You able to create a custom visual that has a specific icon, name, and input variables by changing some files like “script.r”, “pbiviz.json” and “capabilities.json”. The session has all demo and required steps to create a custom visual using R.
Views: 2981 Pragmatic Works
Data Analyst vs Data Engineer vs Data Scientist | Data Analytics Masters Program | Edureka
 
09:08
** Data Analytics Masters' Program: https://www.edureka.co/masters-program/data-analyst-certification ** ** Data Scientist Masters' Program: https://www.edureka.co/masters-program/data-scientist-certification ** This Edureka video on "Data Analyst vs Data Engineer vs Data Scientist" will help you understand the various similarities and differences between them. Also, you will get a complete roadmap along with the skills required to get into a data-related career. Below topics are covered in this video: 1:05 - Who is data analyst, data engineer and data scientist? 2:32 - Roadmap 3:48 - Required skill-sets 5:34 - Roles and Responsibilities 7:16 - Salary Perspective ------------------------------------- Data Science Training Playlist: https://goo.gl/Jg1pJJ Blog Series: https://goo.gl/H2pf8V Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka #dataanalystvsdataengineervsdatascientist #DataScience #DataScienceCertificationTraining ------------------------------------- Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Data Science Training and Certification, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
Views: 42209 edureka!
Blockchain Explained | How Does A Blockchain Work | Blockchain Explained Simply | Simplilearn
 
17:02
This "Blockchain Explained" video will help you understand what is Blockchain, what is Bitcoin, features of Blockchain which includes public distributed ledger, hash encryption, proof of work, mining and will also talk about the fields that use Bitcoin. Bitcoin is a decentralized, digital currency. Bitcoins were created as an incentive for processing payments, in which users can offer their power of computing for verifying and recording payments that go into public ledgers. The blockchain of bitcoin enables verification of transactions anytime, anywhere. However, for Bitcoin to succeed, people should gain a deeper understanding of the ways in which Bitcoin works, without letting their preconceived notions distort the digital currency concept. This Blockchain tutorial is designed for such beginners to give them a deep knowledge on how Blockchain and Bitcoin works. Now, lets deep dive into this video to understand what Blockchain actually is. Below topics are explained in this Blockchain tutorial: 1. What is Blockchain? ( 03:41 ) 2. What is Bitcoin? ( 04:47 ) 3. Features of Blockchain - ( 06:13 ) - Public Distributed Ledger - Hash Encryption - Proof of Work - Mining 4. Other fields that use Blockchain ( 12:57 ) To learn more about Blockchain, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the slides here: https://goo.gl/W1iGEh Watch more videos on Blockchain: https://www.youtube.com/playlist?list=PLEiEAq2VkUUKmhU6SO2P73pTdMZnHOsDB #Whatisblockchain #Blockchain #Blockchaintutorial #Bitcoin #Blockchainonlinetraining #Blockchainforbeginners #BlockchainTechnology #Simplilearn Simplilearn’s Blockchain Certification Training has been designed for developers who want to decipher the global craze surrounding Blockchain, Bitcoin and cryptocurrencies. You’ll learn the core structure and technical mechanisms of Bitcoin, Ethereum, Hyperledger and Multichain Blockchain platforms, use the latest tools to build Blockchain applications, set up your own private Blockchain, deploy smart contracts on Ethereum and gain practical experience with real-world projects. Why learn Blockchain? Blockchain technology is the brainchild of Satoshi Nakamoto, which enables digital information to be distributed. A network of computing nodes makes up the Blockchain. Durability, robustness, success rate, transparency, incorruptibility are some of the enticing characteristics of Blockchain. By design, Blockchain is a decentralized technology which is used by a global network of the computer to manage Bitcoin transactions easily. Many new business applications will result in the usage of Blockchain such as Crowdfunding, smart contracts, supply chain auditing, Internet of Things(IoT), etc. This Blockchain Certification course offers a hands-on training covering relevant topics in cryptocurrency and the wider Blockchain space. From a technological standpoint, you will develop a strong grasp of core Blockchain platforms, understand what Bitcoin is and how it works, learn key vocabulary and concepts commonly used when discussing Blockchain and understand why engineers are motivated to create an app with Ethereum. Hands-on exercises and projects will give you practical experience in real-world Blockchain development scenarios. After completing this course, you will be able to: 1. Apply Bitcoin and Blockchain concepts in business situations 2. Build compelling Blockchain applications using the Ethereum Blockchain 3. Design, test and deploy secure Smart Contracts 4. Use the latest version of Ethereum development tools (Web3 v1.0) 5. Develop Hyperledger Blockchain applications using Composer Framework 6. Model the Blockchain applications using Composer modeling language 7. Develop front-end (client) applications using Composer API 8. Leverage Composer REST Server to design a web-based Blockchain solution 9. Design Hyperledger Fabric Composer Business Network 10. 10. Understand the true purpose and capabilities of Ethereum and Solidity The Blockchain Certification Training Course is recommended for: 1. Developers 2. Technologists interested in learning Ethereum, Hyperledger and Blockchain 3. Technology architects wanting to expand their skills to Blockchain technology 4. Professionals curious to learn how Blockchain technology can change the way we do business 5. Entrepreneurs with technology background interested in realizing their business ideas on the Blockchain Learn more at: https://www.simplilearn.com/blockchain-certification-training?utm_campaign=Blockchain-Explained-pTLlPUhcKCQ&utm_medium=Tutorials&utm_source=youtube For more updates on courses and tips follow us on: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 5103 Simplilearn
Data Mining with Weka - FutureLearn
 
01:49
Data Mining with Weka: online course with FutureLearn from the University of Waikato First session starts 6 March 2017 https://www.futurelearn.com/courses/data-mining-with-weka/ https://twitter.com/WekaMOOC Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 5431 WekaMOOC
Blockchain Tutorial For Beginners - 2 | Blockchain Technology | Blockchain Tutorial | Simplilearn
 
18:49
This Blockchain tutorial will help you understand what is block, how to add 2 blocks at the same time, forks, areas where Blockchain is used, future of Blockchain and at the end you will also see a use case on smart contract. A blockchain is a digitized, decentralized, public ledger of Bitcoin transactions. The technology verifies transactions and creates a “chain” of blocks of data including a timestamp that is linked to other blocks so one block can’t be changed. In simple words, Blockchain is a list of records (blocks) which stores data publicly and in chronological order and mining is the process of adding a block to the Blockchain. Now, let us get started and understand what is Blockchain and its features. Below topics are explained in this Blockchain tutorial: 1. The candidate Block ( 03:14 ) 2. Byzantime fault tolerance ( 04:19 ) 3. Adding 2 blocks at the same time ( 07:53 ) 4. Forks ( 09:51 ) - Soft forks - Hard forks 5. Other areas where Blockchain is used ( 12:38 ) 6. The future of Blockchain ( 13:15 ) 7. Blockchain jobs ( 14:11 ) 8. Use case : Movie ratings smart contract Blockchain Tutorial Part - 1 : https://www.youtube.com/watch?v=iYYf3w4RPDA Find the code here: https://github.com/pjai30/movieRatingApp To learn more about Blockchain, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the Slides here: https://goo.gl/PXeb7h Watch more videos on Blockchain: https://www.youtube.com/playlist?list=PLEiEAq2VkUUKmhU6SO2P73pTdMZnHOsDB #Whatisblockchain #Blockchain #Blockchaintutorial #Bitcoin #Blockchainonlinetraining #Blockchainforbeginners #BlockchainTechnology #Simplilearn Simplilearn’s Blockchain Certification Training has been designed for developers who want to decipher the global craze surrounding Blockchain, Bitcoin and cryptocurrencies. You’ll learn the core structure and technical mechanisms of Bitcoin, Ethereum, Hyperledger and Multichain Blockchain platforms, use the latest tools to build Blockchain applications, set up your own private Blockchain, deploy smart contracts on Ethereum and gain practical experience with real-world projects. Why learn Blockchain? Blockchain technology is the brainchild of Satoshi Nakamoto, which enables digital information to be distributed. A network of computing nodes makes up the Blockchain. Durability, robustness, success rate, transparency, incorruptibility are some of the enticing characteristics of Blockchain. By design, Blockchain is a decentralized technology which is used by a global network of the computer to manage Bitcoin transactions easily. Many new business applications will result in the usage of Blockchain such as Crowdfunding, smart contracts, supply chain auditing, etc. This Blockchain Certification course offers a hands-on training covering relevant topics in cryptocurrency and the wider Blockchain space. From a technological standpoint, you will develop a strong grasp of core Blockchain platforms, understand what Bitcoin is and how it works, learn key vocabulary and concepts commonly used when discussing Blockchain and understand why engineers are motivated to create an app with Ethereum. After completing this course, you will be able to: 1. Apply Bitcoin and Blockchain concepts in business situations 2. Build compelling Blockchain applications using the Ethereum Blockchain 3. Design, test and deploy secure Smart Contracts 4. Use the latest version of Ethereum development tools (Web3 v1.0) 5. Develop Hyperledger Blockchain applications using Composer Framework 6. Model the Blockchain applications using Composer modeling language 7. Develop front-end (client) applications using Composer API 8. Leverage Composer REST Server to design a web-based Blockchain solution 9. Design Hyperledger Fabric Composer Business Network 10. 10. Understand the true purpose and capabilities of Ethereum and Solidity The Blockchain Certification Training Course is recommended for: 1. Developers 2. Technologists interested in learning Ethereum, Hyperledger and Blockchain 3. Technology architects wanting to expand their skills to Blockchain technology 4. Professionals curious to learn how Blockchain technology can change the way we do business 5. Entrepreneurs with technology background interested in realizing their business ideas on the Blockchain Learn more at: https://www.simplilearn.com/blockchain-certification-training?utm_campaign=Blockchain-Tutorial-For-Beginners-Part1-ov8nVP6dowc&utm_medium=Tutorials&utm_source=youtube For more updates on courses and tips follow us on: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 2567 Simplilearn
Twitter Application of the Day - Avoid Suspension
 
04:31
http://www.twitterright.com Follow the rules. Be prudent with your tweets to avoid suspension. Learn how to use twitter with twitter tools, twitter videos and twitter tutorials at Twitter Right blog.
Turing Lecture: Data science or data humanities? - Melissa Terras
 
01:25:57
Opportunities, barriers, and rewards in digitally-led analysis of history, culture and society About the event What are the opportunities, issues, and rewards for researchers developing data-led approaches to answer research questions in the Arts and Humanities? How can we build and utilise appropriate computational methods for the analysis of our past and present societies? What possibilities and barriers are there in working in this crossover point from data science to the humanities? And how can the humanities contribute to development of data science approaches? From the development of Handwritten Text Recognition for archival material, and the mining of millions of words of historical newspaper archives, this talk will showcase a range of innovative international research projects, whilst also giving pointers on how others can approach this interdisciplinary space successfully. In addition, it will raise issues of how tricky yet rewarding “interdisciplinary research” – which we are all now being encouraged to do – can be. About the speaker Melissa Terras is the Professor of Digital Cultural Heritage at the University of Edinburgh‘s College of Arts, Humanities, and Social Sciences, leading digital aspects of research within CAHSS, and Director of Research in the new Edinburgh Futures Institute. Her research focuses on the use of computational techniques to enable research in the arts, humanities, and wider cultural heritage and information environment that would otherwise be impossible. With a background in Classical Art History and English Literature (MA, University of Glasgow), and Computing Science (MSc IT with distinction in Software and Systems, University of Glasgow), her doctorate (Engineering, University of Oxford) examined how to use image processing and machine learning to interpret and read deteriorated Ancient Roman texts. She is an Honorary Professor of Digital Humanities in UCL Department of Information Studies, where she was employed from 2003-2017, Directing UCL Centre for Digital Humanities from 2013. Books include “Image to Interpretation: An Intelligent System to Aid Historians in Reading the Vindolanda Texts” (2006, Oxford University Press) and and “Defining Digital Humanities: A Reader” (Ashgate 2013) which has been translated into Russian and Chinese. She is a Trustee of the National Library of Scotland, serves on the Board of Curators of the University of Oxford Libraries. is a Fellow of the Chartered Institute of Library and Information Professionals, and Fellow of the British Computer Society. You can generally find her on twitter @melissaterras.
Analyzing Big Data with Twitter - Lecture 4 - Apache Pig at Twitter
 
01:21:40
http://blogs.ischool.berkeley.edu/i290-abdt-s12/ Jon Coveney gives an in-depth tutorial on Apache Pig. Course: Information 290. Analyzing Big Data with Twitter School of Information UC Berkeley Prof. Marti Hearst Course description: How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered. This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.
Data Science Tutorial for Beginners - 1 | What is Data Science? | Data Analytics Tools | Edureka
 
02:32:56
( Data Science Training - https://www.edureka.co/data-science ) Data Science Blog Series: https://goo.gl/1CKTyN http://www.edureka.co/data-science Please write back to us at [email protected] or call us at +91-8880862004 for more information. Data Science is all about extracting knowledge from data. Data Science is the integration of methods from mathematics, probability models, machine learning, computer programming, statistics, data engineering, pattern recognition and learning, visualization, uncertainty modelling, data warehousing, and high performance computing with the goal of extracting meaning from data and creating data products. This interdisciplinary and cross-functional field leads to decisions that move an organization forward in terms of proposed investment, decisions regarding a product or business strategy. Data Science is a buzzword, often used interchangeably with analytics or big data. At times, Analytics is synonymous with Data Science, but at times it represents something else. A Data Scientist using raw data to build a predictive behaviour model, falls in to the category of analytics. About the Data Science Course at edureka! - This Data Science course is designed to provide knowledge and skills to become a successful Data Scientist. The course covers a range of Hadoop, R and Machine Learning Techniques encompassing the complete Data Science study. Course Objectives After the completion of the Data science Course at Edureka, you should be able to: Gain an insight into the 'Roles' played by a Data Scientist. Analyse Big Data using Hadoop and R. Understand the Data Analysis Life Cycle. Use tools such as 'Sqoop' and 'Flume' for acquiring data in Hadoop Cluster. Acquire data with different file formats like JSON, XML, CSV and Binary. Learn tools and techniques for sampling and filtering data, and data transformation. Understand techniques of Natural Language Processing and Text Analysis. Statistically analyse and explore data using R. Create predictive using Hadoop Mappers and Reducers. Understand various Machine Learning Techniques and their implementation these using Apache Mahout. Gain insight into the visualisation and optimisation of data. Who should go for this course? This course is designed for all those who want to learn machine learning techniques and wish to apply these techniques on Big Data. The course is amalgamation of two powerful open source tools: 'R' language and Hadoop software framework. You will learn how to explore data quantitatively using tools like Sqoop and Flume, write Hadoop MapReduce Jobs, perform Text Analysis and implement Language Processing, learn Machine Learning techniques using Mahout, and optimize and visualize the results using programming language 'R' and Apache Mahout. This course is for you if you are: A SAS, SPSS Analytics Professional. A Hadoop Professional working on Database management and streaming of Big Data. An 'R' professional who wants to apply Statistical techniques on Big Data. A Statistician who wants to understand Data Science methodologies to implement the statistics methods and techniques on Big data. Any Business Analyst who is working on creating reports and dashboards. Pre-requisites Some of the prerequisites for learning Data Science are familiarity with Hadoop, Machine Learning and knowledge of R (recommended not mandatory as these concepts will also be covered during the course). Also, having a statistical background will be an added advantage. Why Learn Data Science? 'Data Science' is a term which came into popularity in past decade. Data Science is the process of extracting valuable insights from "data". It is the right time to learn Data science because: We are living in the Big Data Era, Data Science is becoming a very promising field to harness and process huge volumes of data generated from various sources. A data scientist has a dual role -- that of an "Analyst" as well as that of an "Artist"! Data scientists are very curious, who love large amount of data, and more than that, they love to play with such huge data to reach important inferences and spot trends. You could be one of them! As 'Data Science' is an emerging field, there is a plethora of opportunities available world across. Just browse through any of the job portals; you will be taken aback by the number of job openings available for Data scientists in different industries, whether it is IT or healthcare, Retail or Government offices or Academics, Life Sciences, Oceanography, etc. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 218426 edureka!
Twitter geomap quickstart video
 
02:59
A short demonstration of a web application that browses a subset of Twitter data. It allows the user to examine the geospatial positions and full text content of tweets.
Views: 109 Curtis Lisle
BADM 1.2: Data Mining in a Nutshell
 
11:04
What is Data Mining? How is it different from Statistics? This video was created by Professor Galit Shmueli and has been used as part of blended and online courses on Business Analytics using Data Mining. It is part of a series of 37 videos, all of which are available on YouTube. For more information: http://www.dataminingbook.com https://www.twitter.com/gshmueli https://www.facebook.com/dataminingbook Here is the complete list of the videos: • Welcome to Business Analytics Using Data Mining (BADM) • BADM 1.1: Data Mining Applications • BADM 1.2: Data Mining in a Nutshell • BADM 1.3: The Holdout Set • BADM 2.1: Data Visualization • BADM 2.2: Data Preparation • BADM 3.1: PCA Part 1 • BADM 3.2: PCA Part 2 • BADM 3.3: Dimension Reduction Approaches • BADM 4.1: Linear Regression for Descriptive Modeling Part 1 • BADM 4.2 Linear Regression for Descriptive Modeling Part 2 • BADM 4.3 Linear Regression for Prediction Part 1 • BADM 4.4 Linear Regression for Prediction Part 2 • BADM 5.1 Clustering Examples • BADM 5.2 Hierarchical Clustering Part 1 • BADM 5.3 Hierarchical Clustering Part 2 • BADM 5.4 K-Means Clustering • BADM 6.1 Classification Goals • BADM 6.2 Classification Performance Part 1: The Naive Rule • BADM 6.3 Classification Performance Part 2 • BADM 6.4 Classification Performance Part 3 • BADM 7.1 K-Nearest Neighbors • BADM 7.2 Naive Bayes • BADM 8.1 Classification and Regression Trees Part 1 • BADM 8.2 Classification and Regression Trees Part 2 • BADM 8.3 Classification and Regression Trees Part 3 • BADM 9.1 Logistic Regression for Profiling • BADM 9.2 Logistic Regression for Classification • BADM 10 Multi-Class Classification • BADM 11 Ensembles • BADM 12.1 Association Rules Part 1 • BADM 12.2 Association Rules Part 2 • Neural Networks: Part I • Neural Networks: Part II • Discriminant Analysis (Part 1) • Discriminant Analysis: Statistical Distance (Part 2) • Discriminant Analysis: Misclassification costs and over-sampling (Part 3)
Views: 1371 Galit Shmueli
Analyzing Big Data with Twitter - Lec. 2 - Growing a Human-Scale Service & the Twitter Ecosystem
 
01:27:11
http://blogs.ischool.berkeley.edu/i290-abdt-s12/ Lecture 2 - August 28, 2012 Growing a Human-Scale Consumer Service Othman Laraki Introduction to the Twitter Software Ecosystem Raffi Krikorian Course: Information 290. Analyzing Big Data with Twitter School of Information UC Berkeley Prof. Marti Hearst Course description: How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered. This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.
Amber Baldet on Surveillance Capitalism
 
01:07:20
In this episode, I talk with Amber Baldet from Clovyr. We talk about surveillance capitalism and the increasing hunger for data by Silicon Valley behemoths, the impact on society as well as question recent Coinbase decisions and Web 3.0. LISTEN TO THE FULL EPISODE HERE AND ACCESS LINKS TO THE SHOW NOTES https://www.whatbitcoindid.com/podcast/amber-baldet-on-surveillance-capitalism WHERE TO FIND THE SHOW → My website: https://www.whatbitcoindid.com/podcast/ → iTunes: https://apple.co/2OOlzVV → Spotify: https://spoti.fi/2ygc4W1 → Stitcher: https://bit.ly/2IQO8fX → SoundCloud: https://bit.ly/2CGSVQR → YouTube: https://bit.ly/2pR3s3g → TuneIn: https://bit.ly/2ywystr LISTEN TO OLD EPISODES → By guest: https://www.whatbitcoindid.com/guests/ → By topic: https://www.whatbitcoindid.com/topics/ → Transcriptions: https://www.whatbitcoindid.com/transcriptions/ SUPPORT THE SHOW → https://www.whatbitcoindid.com/sponsorship/ → Become a Patron: https://www.patreon.com/whatbitcoindid/ → Subscribe on iTunes → Leave a review on iTunes → Share the show out with your friends and family on social media → Drop me a line on [email protected] WHERE TO FOLLOW ME: → Twitter: https://twitter.com/whatbitcoindid/ → Medium: https://medium.com/@whatbitcoindid/ → Instagram: http://instagram.com/whatbitcoindid/ → Facebook: https://www.facebook.com/whatbitcoindid/ → YouTube: https://www.youtube.com/whatbitcoindid/ → Website: https://www.whatbitcoindid.com/ → Email list: https://www.whatbitcoindid.com/subscribe/ LEARN ABOUT BITCOIN & CRYPTO: → Step by Step Guide: https://www.whatbitcoindid.com/beginners-guide → Training: https://www.whatbitcoindid.com/training/ → Resources: https://www.whatbitcoindid.com/resources/ ***** “Every tool is a weapon if you hold it right.” — Amber Baldet Interview location: New York Interview date: Wednesday 6th March, 2019 Company: Clovyr Role: Founder The line between data collection for commercial use and surveillance by the state has become blurred. Where the NSA tracks online user activity for crime prevention, Silicon Valley behemoths have become increasingly hungry for user data with the goal of building ever more targeted advertising solutions. Within the world of cryptocurrencies, the requirement for KYC/AML checks has blurred the lines between data collection and state tracking. Privacy is often touted as a fundamental human right, but our moves are tracked both online and in the real world at an increasingly alarming rate. In this interview I talk with Amber Baldet about the growth of surveillance capitalism, the impact on society as well as question recent Coinbase decisions and Web 3.0. ***** 00:04:17: Introductions 00:05:28: Amber’s perspective on the present day Crypto markets 00:07:45: What Amber is working on at Clovyr 00:11:41: Why is privacy not viewed as a pressing issue in design 00:15:05: Discussing the concept of surveillance capitalism 00:22:16: How can we use data without the sinister surveillance aspect integrated? 00:26:55: Discussions around the sinister side of data collection 00:29:02: Amber’s opinion on Coinbase purchasing Neutrino 00:37:49: Amber’s Background story 00:41:02: Chain analysis and the implications surrounding surveillance in Crypto 00:43:21: The importance of privacy in Bitcoin and other cryptocurrencies 00:51:14: Discussing decentralize web architectures and Web 3.0 01:01:51: Outlook for the future 01:03:25: How to stay in touch with Amber and final comments
Views: 1953 whatbitcoindid
Brand and Design your MeetUp group page with logo and background image
 
06:05
Don't use BMP files. JPG is best!!! http://robcubbon.com
Views: 9729 Rob Cubbon
Social Media Mining
 
02:22
Social Media Mining
Views: 463 WMAR-2 News