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Python Data Mining
 
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Views: 27519 Alex Stoykov
Learn Python Programming - 3 - Data Mining with Python
 
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Learn Python Programming - 3 - Data Mining with Python In this video we will learn to code a program which grabs the data which is saved in a excel file. This code will be coded with python. By Kovid Raj Panthy (Coder Kovid)
Views: 3198 Coder Kovid
Intro to Data Analysis / Visualization with Python, Matplotlib and Pandas | Matplotlib Tutorial
 
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Python data analysis / data science tutorial. Let’s go! For more videos like this, I’d recommend my course here: https://www.csdojo.io/moredata Sample data and sample code: https://www.csdojo.io/data My explanation about Jupyter Notebook and Anaconda: https://bit.ly/2JAtjF8 Also, keep in touch on Twitter: https://twitter.com/ykdojo And Facebook: https://www.facebook.com/entercsdojo Outline - check the comment section for a clickable version: 0:37: Why data visualization? 1:05: Why Python? 1:39: Why Matplotlib? 2:23: Installing Jupyter through Anaconda 3:20: Launching Jupyter 3:41: DEMO begins: create a folder and download data 4:27: Create a new Jupyter Notebook file 5:09: Importing libraries 6:04: Simple examples of how to use Matplotlib / Pyplot 7:21: Plotting multiple lines 8:46: Importing data from a CSV file 10:46: Plotting data you’ve imported 13:19: Using a third argument in the plot() function 13:42: A real analysis with a real data set - loading data 14:49: Isolating the data for the U.S. and China 16:29: Plotting US and China’s population growth 18:22: Comparing relative growths instead of the absolute amount 21:21: About how to get more videos like this - it’s at https://www.csdojo.io/moredata
Views: 326678 CS Dojo
Data mining and integration with Python
 
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There is an abundance of data in social media sites (Wikipedia, Facebook, Instagram, etc.) which can be accessed through web APIs. But how do we know that the data from the Wikipedia article on "Golden Gate Bridge" goes along with the data from "Golden Gate Bridge" Facebook page? This represents an important question about integrating data from various sources. In this talk, I'll outline important aspects of structured data mining, integration and entity resolution methods in a scalable system.
Views: 5694 PyTexas
Python For Data Science - 2018 | Become Data Scientist
 
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This tutorial introduces users to Python for data science. From data cleaning to model building, we will work through a series of short examples together using some real-world health inspection data. Attendees will have their hands on the keyboard, using the Python standard library and pandas to clean data and scikit-learn to build some models. Speaker: Skipper Seabold Originally Published at PYCON 2018 Slides can be found at: https://speakerdeck.com/pycon2018 and https://github.com/PyCon/2018-slides Please Subscribe my channel to motivate me . Subscribe Our Channel : https://goo.gl/BlFui4 For Fun - https://www.youtube.com/channel/UC6i0... Connect with us on social media: Facebook: https://www.facebook.com/mtechviral Pawan Kumar - https://www.facebook.com/imthepk Ask Pawan Kumar - https://www.facebook.com/thepawankumaar Instagram - https://instagram.com/codepur_ka_superhero Twitter: https://twitter.com/imthepk LIKE | SHARE | SUBSCRIBE FOR MORE VIDEOS LIKE THIS THANKS FOR WATCHING!
Views: 34262 MTECHVIRAL
Data Analysis of Uber trip data using Python, Pandas, and Jupyter Notebook
 
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https://github.com/mnd-af/src/blob/master/2017/06/04/Uber%20Data%20Analysis.ipynb
Views: 37305 MandarinaCS
Introduction/tutorial to visual programming in Orange (python-based) a Data Mining Tool
 
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Sumaiya Iqbal, Broad Institute of MIT and Hardvard & MGH is giving a overview of Orange a python-based Data Mining Tool. This tool is useful for individuals with and without programming background. Sumaiya gives examples for hierarchical clustering, PCA, prediction and text mining.
Views: 4703 Dennis Lal
Making Predictions with Data and Python : Predicting Credit Card Default | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2eZbdPP]. Demonstrate how to build, evaluate and compare different classification models for predicting credit card default and use the best model to make predictions. • Introduce, load and prepare data for modeling • Show how to build different classification models • Show how to evaluate models and use the best to make predictions For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 35564 Packt Video
Python for Data Analysis Tutorial - Setup, Read File & First Chart
 
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How can we get started with data analysis or data science - so for example read and change data and also create our first quick chart - in Python? Besides Python, all we need is Pandas and Matplotlib. Doesn't sound familiar to you? Let's clear things up and get started in this video! ---------- Learn Python from scratch: https://www.udemy.com/learn-python-by-building-a-blockchain-cryptocurrency/?couponCode=ACAD_M Download the source file: https://a.storyblok.com/f/42126/x/279bce29a2/revenue-profit.csv Want to learn something totally different? Check out all other courses: https://academind.com/learn/our-courses ---------- • You can follow Max on Twitter (@maxedapps). • And you should of course also follow @academind_real. • You can also find us on Facebook.(https://www.facebook.com/academindchannel/) • Or visit our Website (https://www.academind.com) and subscribe to our newsletter! See you in the videos! ---------- Academind is your source for online education in the areas of web development, frontend web development, backend web development, programming, coding and data science! No matter if you are looking for a tutorial, a course, a crash course, an introduction, an online tutorial or any related video, we try our best to offer you the content you are looking for. Our topics include Angular, React, Vue, Html, CSS, JavaScript, TypeScript, Redux, Nuxt.js, RxJs, Bootstrap, Laravel, Node.js, Progressive Web Apps (PWA), Ionic, React Native, Regular Expressions (RegEx), Stencil, Power BI, Amazon Web Services (AWS), Firebase or other topics, make sure to have a look at this channel or at academind.com to find the learning resource of your choice!
Views: 28007 Academind
Predicting Stock Prices - Learn Python for Data Science #4
 
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In this video, we build an Apple Stock Prediction script in 40 lines of Python using the scikit-learn library and plot the graph using the matplotlib library. The challenge for this video is here: https://github.com/llSourcell/predicting_stock_prices Victor's winning recommender code: https://github.com/ciurana2016/recommender_system_py Kevin's runner-up code: https://github.com/Krewn/learner/blob/master/FieldPredictor.py#L62 I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Stock prediction with Tensorflow: https://nicholastsmith.wordpress.com/2016/04/20/stock-market-prediction-using-multi-layer-perceptrons-with-tensorflow/ Another great stock prediction tutorial: http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ This guy made 500K doing ML stuff with stocks: http://jspauld.com/post/35126549635/how-i-made-500k-with-machine-learning-and-hft Please share this video, like, comment and subscribe! That's what keeps me going. and please support me on Patreon!: https://www.patreon.com/user?u=3191693 Check out this youtube channel for some more cool Python tutorials: https://www.youtube.com/watch?v=RZF17FfRIIo Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 606521 Siraj Raval
Introduction - Learn Python for Data Science #1
 
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Welcome to the 1st Episode of Learn Python for Data Science! This series will teach you Python and Data Science at the same time! In this video we install Python and our text editor (Sublime Text), then build a gender classifier using the sci-kit learn library in just about 10 lines of code. Please subscribe & share this video if you liked it! The code for this video is here: https://github.com/llSourcell/gender_classification_challenge I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Download Python here: https://www.python.org/downloads/ Download Sublime Text here: https://www.sublimetext.com/3 Some Great simple sci-kit learn examples here: https://github.com/chribsen/simple-machine-learning-examples and the official scikit website: http://scikit-learn.org/ Highly recommend this online book as supplementary reading material: https://learnpythonthehardway.org/book/ Wondering when to use which model? This chart helps, but keep in mind deep neural nets outperform pretty much any model given enough data and computing power. so use these when you don't have access to loads of data and compute: http://scikit-learn.org/stable/tutorial/machine_learning_map/ Thank you guys for watching! Subscribe, like, and comment! That's what keeps me going. Feel free to support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 529577 Siraj Raval
Twitter Sentiment Analysis - Learn Python for Data Science #2
 
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In this video we'll be building our own Twitter Sentiment Analyzer in just 14 lines of Python. It will be able to search twitter for a list of tweets about any topic we want, then analyze each tweet to see how positive or negative it's emotion is. The coding challenge for this video is here: https://github.com/llSourcell/twitter_sentiment_challenge Naresh's winning code from last episode: https://github.com/Naresh1318/GenderClassifier/blob/master/Run_Code.py Victor's Runner up code from last episode: https://github.com/Victor-Mazzei/ml-gender-python/blob/master/gender.py I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ More on TextBlob: https://textblob.readthedocs.io/en/dev/ Great info on Sentiment Analysis: https://www.quora.com/How-does-sentiment-analysis-work Great sentiment analysis api: http://www.alchemyapi.com/products/alchemylanguage/sentiment-analysis Read over these course notes if you wanna become an NLP god: http://cs224d.stanford.edu/syllabus.html Best book to become a Python god: https://learnpythonthehardway.org/ Please share this video, like, comment and subscribe! That's what keeps me going. Feel free to support me on Patreon: https://www.patreon.com/user?u=3191693 Two Minute Papers Link: https://www.youtube.com/playlist?list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 287979 Siraj Raval
Practical Data Mining with Python
 
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Bilal Aslam (bilalaslam.com) gives an overview of data mining with Python at the Eastside Incubator (www.EastsideIncubator.com). Not the greatest sound quality, but if you crank it you can hear!
Views: 9582 Eastsi Incub
Data Analysis with Python for Excel Users
 
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A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. See http://apmonitor.com/che263/index.php/Main/PythonDataAnalysis
Views: 192190 APMonitor.com
Mining data on Facebook with Python: 1- Setting up our app for mining data on Facebook
 
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In this tutorial we will set up our app to mine data from Facebook. We will be introduces to the Facebook API Graph and setting up user token access. Let's connect out app to communicate with the Graph API to get started mining data on this huge platform. ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 19215 Sukhvinder Singh
Kenapa Python | Python untuk Data Mining Tutorial 1
 
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Python untuk Data Mining | Python for Data Mining Tutorial 1 Data Mining menggunakan bahasa pemrograman Python. Dari Mulai: 1. Alasan Kenapa menggunakan Python 2. Machine Learning Library di Python 3. Komponen bahasa pemrograman Python 4. Virtual environment di Python 5. Dasar-dasar pemrograman Python 6. Numpy, scipy, pandas, matplotlib 7. Data Mining dengan Python 8. Analisis data menggunakan Python 9. Dan sebagainya #Python #DataMining #MachineLearning #DataAnalysis #scikit-learn
Views: 4916 Rischan Mafrur
Decision Tree Algorithm | Decision Tree in Python | Machine Learning Algorithms | Edureka
 
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** Machine Learning with Python : https://www.edureka.co/machine-learning-certification-training ** This Edureka video on Decision Tree Algorithm in Python will take you through the fundamentals of decision tree machine learning algorithm concepts and its demo in Python. Below are the topics covered in this tutorial: 1. What is Classification? 2. Types of Classification 3. Classification Use Case 4. What is Decision Tree? 5. Decision Tree Terminology 6. Visualizing a Decision Tree 7 Writing a Decision Tree Classifier fro Scratch in Python using CART Algorithm Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Machine Learning Playlist: https://goo.gl/UxjTxm #decisiontree #decisiontreepython #machinelearningalgorithms - - - - - - - - - - - - - - - - - About the Course Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience. After completing this Machine Learning Certification Training using Python, you should be able to: Gain insight into the 'Roles' played by a Machine Learning Engineer Automate data analysis using python Describe Machine Learning Work with real-time data Learn tools and techniques for predictive modeling Discuss Machine Learning algorithms and their implementation Validate Machine Learning algorithms Explain Time Series and it’s related concepts Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Machine Learning with Python? Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning. 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: 85570 edureka!
Apriori Algorithm (Associated Learning) - Fun and Easy Machine Learning
 
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Apriori Algorithm (Associated Learning) - Fun and Easy Machine Learning ►FREE YOLO GIFT - http://augmentedstartups.info/yolofreegiftsp ►KERAS Course - https://www.udemy.com/machine-learning-fun-and-easy-using-python-and-keras/?couponCode=YOUTUBE_ML Limited Time - Discount Coupon Apriori Algorithm The Apriori algorithm is a classical algorithm in data mining that we can use for these sorts of applications (i.e. recommender engines). So It is used for mining frequent item sets and relevant association rules. It is devised to operate on a database containing a lot of transactions, for instance, items brought by customers in a store. It is very important for effective Market Basket Analysis and it helps the customers in purchasing their items with more ease which increases the sales of the markets. It has also been used in the field of healthcare for the detection of adverse drug reactions. A key concept in Apriori algorithm is that it assumes that: 1. All subsets of a frequent item sets must be frequent 2. Similarly, for any infrequent item set, all its supersets must be infrequent too. ------------------------------------------------------------ Support us on Patreon ►AugmentedStartups.info/Patreon Chat to us on Discord ►AugmentedStartups.info/discord Interact with us on Facebook ►AugmentedStartups.info/Facebook Check my latest work on Instagram ►AugmentedStartups.info/instagram Learn Advanced Tutorials on Udemy ►AugmentedStartups.info/udemy ------------------------------------------------------------ To learn more on Artificial Intelligence, Augmented Reality IoT, Deep Learning FPGAs, Arduinos, PCB Design and Image Processing then check out http://augmentedstartups.info/home Please Like and Subscribe for more videos :)
Views: 74170 Augmented Startups
Intro - Mining Data from Social Media with Python
 
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Intro to video tutorial series for Mining Data from Social Media with Python ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 13326 Sukhvinder Singh
Customer Segmentation in Python - PyConSG 2016
 
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Speaker: Mao Ting Description By segmenting customers into groups with distinct patterns, businesses can target them more effectively with customized marketing and product features. I'll dive into a few machine learning and statistical techniques to extract insights from customer data, and demonstrate how to execute them on real data using Python and open-source libraries. Abstract I will go through clustering and decision tree analysis using sciki-learn and two-sample t test using scipy. We will learn the intuition for each technique, the math behind them, and how to implement them and evaluate the results using Python. I will be using open-source data for the demonstration, and show what insights you can extract from actual data using these techniques. Event Page: https://pycon.sg Produced by Engineers.SG Help us caption & translate this video! http://amara.org/v/P6SD/
Views: 19579 Engineers.SG
Natural Language Processing (NLP) & Text Mining Tutorial Using NLTK | NLP Training | Edureka
 
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** 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: 61038 edureka!
Data Mining (Minería de datos) | Práctica en python
 
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**Información complementaria** 1) El IDE usado es ANACONDA (Una vez instalado ANACONDA ya tienes todas las herramientas de python, no es necesario instalar python aparte) 2) En mi caso tengo S.O. Mac, tuve que guardar los documentos *.txt como UTF-8, si se guardan en la codificación por defecto la información se guarda como 0's y 1's por tanto el programa aquí mostrado no funcionará. Link de programa del video: http://clasesdesarrollosoftware.blogspot.mx/2016/10/programa-en-python-sobre-data-mining.html Contacto: Facebook: Ulyses Rico Rea Twitter: @ulysesricord
Views: 9891 Software development
Twitter Data Mining using Python
 
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For complete professional training visit at: http://www.bisptrainings.com/course/Python-for-Beginners Follow us on Facebook: https://www.facebook.com/bisptrainings/ Follow us on Twitter: https://twitter.com/bisptrainings Email: [email protected] Call us: +91 975-275-3753 or +1 386-279-6856
Views: 29294 Amit Sharma
Cleaning Data In Python Using Pandas In Data Mining Example, Statistics With Python For Data Science
 
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In this Data Mining Example Tutorial, we learn how to clean our data set using Python and Pandas. We clean Billboard data set by headly. we perform several python data cleaning operations on our Data set which is csv file. This will be the best pandas tutorial in data science you will have ever watched. 🔷🔷🔷🔷🔷🔷🔷 Jupyter NOtebooks and Data Sets for Practice: https://github.com/theengineeringworld/statistics-using-python 🔷🔷🔷🔷🔷🔷🔷 Data Cleaning Steps and Methods, How to Clean Data for Analysis With Pandas In Python [Example] 🐼 https://youtu.be/GMxCL0PBHzA Data Wrangling With Python Using Pandas, Data Science For Beginners, Statistics Using Python 🐍🐼 https://youtu.be/tqv3sL67sC8 Cleaning Data In Python For Statistical Analysis Using Pandas, Big Data & Data Science For Beginners https://youtu.be/4own4ojgbnQ Exploratory Data Analysis In Python, Interactive Data Visualization [Course] With Python and Pandas https://youtu.be/VdWfB30QTYI 🔷🔷🔷🔷🔷🔷🔷 *** Complete Python Programming Playlists *** * Python Data Science https://www.youtube.com/watch?v=Uct_EbThV1E&list=PLZ7s-Z1aAtmIbaEj_PtUqkqdmI1k7libK * NumPy Data Science Essential Training with Python 3 https://www.youtube.com/playlist?list=PLZ7s-Z1aAtmIRpnGQGMTvV3AGdDK37d2b * Python 3.6.4 Tutorial can be fund here: https://www.youtube.com/watch?v=D0FrzbmWoys&list=PLZ7s-Z1aAtmKVb0fpKyINNeSbFSNkLTjQ * Python Smart Programming in Jupyter Notebook: https://www.youtube.com/watch?v=FkJI8np1gV8&list=PLZ7s-Z1aAtmIVV0dp08_X-yDGrIlTExd2 * Python Coding Interview: https://www.youtube.com/watch?v=wwtzs7vTG50&list=PLZ7s-Z1aAtmJqtN1A3ydeMk0JoD3Lvt9g
Views: 2405 TheEngineeringWorld
web scraping using python for beginners
 
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Learn Python here: https://courses.learncodeonline.in/learn/Python3-course In this video, we will talk about basics of web scraping using python. This is a video for total beginners, please comment if you want more videos on web scraping fb: https://www.facebook.com/HiteshChoudharyPage homepage: http://www.hiteshChoudhary.com Download LearnCodeOnline.in app from Google play store and Apple App store
Views: 204101 Hitesh Choudhary
Social Media Mining & Scrapping with Python
 
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Social media crawler/scrapper that dumps images, tweets, captions, external links and hashtags from Instagram and Twitter in an organized form. It also shows the most relevant hashtags with their frequency of occurrence in the posts. Github Link https://github.com/the-javapocalypse/Social-Media-Scrapper/blob/master/README.md Twitter App https://apps.twitter.com/ Please Subscribe! And like. And comment. That's what keeps me going. Follow Me Facebook: https://www.facebook.com/javapocalypse Instagram: https://www.instagram.com/javapocalypse
Views: 3748 Javapocalypse
Introduction to Data Mining and Text Mining #2 (Python & Jupyter)
 
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Introduction to Data Mining and Text Mining - Part 2 - Python Introduction - Anaconda Installation (Data Science Distribution of Python) - Jupyter Introduction (Next Generation Engineering Notebook) “Hello World!” in Jupyter, and so on. by Kanda Tiwatthanont (Phawattanakul)
Views: 1968 Kanda
Intro to Web Scraping with Python and Beautiful Soup
 
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Web scraping is a very powerful tool to learn for any data professional. With web scraping the entire internet becomes your database. In this tutorial we show you how to parse a web page into a data file (csv) using a Python package called BeautifulSoup. In this example, we web scrape graphics cards from NewEgg.com. Sublime: https://www.sublimetext.com/3 Anaconda: https://www.anaconda.com/distribution/#download-section If you are not seeing the command line, follow this tutorial: https://www.tenforums.com/tutorials/72024-open-command-window-here-add-windows-10-a.html -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz5HN0 Watch the latest video tutorials here: https://hubs.ly/H0hz5SV0 See what our past attendees are saying here: https://hubs.ly/H0hz5K20 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 800 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo #webscraping #python
Views: 560537 Data Science Dojo
Mastering Data Analysis With Python Pandas & Matplotlib 2018
 
04:37:05
Welcome! “Mastering Data Analysis With Python Pandas & Matplotlib 2018” is an excellent choice for both beginners and experts looking to expand their knowledge in Machine Learning field.Data Analysis is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories and hypotheses.Mastering Data Analysis With Python Pandas & Matplotlib 2018 offers in-depth video tutorials in which we’ll dive into tons of different datasets, short and long, broken and pristine. I’ll take you step-by-step through Data Analysis process using the most powerful python libraries (Numpy, Pandas and Matplotlib), from installation to visualization! . tutorials include: Installing. Creating. Accessing. Applying arithmetic operations. Reindexing. Slicing. Tidying up. Handling missing data. Handling duplicated data. Concatenating. Grouping. Aggregating. deleting. visualizing.
Views: 19267 Tech Giant
Data Cleaning Tutorial (2018) | Cleaning Data With Python and Pandas
 
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This data cleaning tutorial will introduce you to Python's Pandas Library in 2018. Check out our website for the best Data Science tips in 2018: https://www.dataoptimal.com Subscribe for even more Data Science tutorials! https://bit.ly/2J2O5N8 Follow us on Twitter! https://twitter.com/DataOptimal **Video Resources** Full article: https://www.dataoptimal.com/data-cleaning-with-python-2018/ Dataset: https://github.com/dataoptimal/videos/tree/master/cleaning%20messy%20data%20with%20pandas Pandas link: http://pandas.pydata.org/pandas-docs/version/0.21/indexing.html#indexing-label Error handling in Python: https://docs.python.org/3/tutorial/errors.html Matt Brems material on missing values: https://github.com/matthewbrems/ODSC-missing-data-may-18/blob/master/Analysis%20with%20Missing%20Data.pdf It's the start of a new project and you're excited to apply some machine learning models. You take a look at the data and quickly realize it's an absolute mess. According to IBM Data Analytics you can expect to spend up to 80% of your time on a project cleaning data. There's all different types of messy data, but today we're going to focus on one of the most common, missing values. We'll take a look at standard types that Pandas recognizes out of the box. Next we'll take a look at some non-standard types. These are inputs that Pandas won't automatically recognize as missing values. After that we'll take a look at unexpected types. Let's say you have a column of names that contains a 12, technically that's a missing value. After we've finished detecting missing values we'll learn how to summarize and do simple replacements.
Views: 14245 DataOptimal
Twitter API with Python: Part 1 -- Streaming Live Tweets
 
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In this video, we make use of the Tweepy Python module to stream live tweets directly from Twitter in real-time. In order to follow along, you will require: 1. A Twitter account, 2. Python. Assuming you have both of these, go ahead and install the "tweepy" module by running the following command inside a terminal shell. pip install tweepy Once we have this, we make a Twitter application that will be used to interface with Python code we will write, and allow us to stream and process live tweets. After creating the Twitter application, we will leverage the "tweepy" module to stream the tweets. Relevant Links: Part 1: https://www.youtube.com/watch?v=wlnx-7cm4Gg Part 2: https://www.youtube.com/watch?v=rhBZqEWsZU4 Part 3: https://www.youtube.com/watch?v=WX0MDddgpA4 Part 4: https://www.youtube.com/watch?v=w9tAoscq3C4 Part 5: https://www.youtube.com/watch?v=pdnTPUFF4gA Tweepy Website: http://www.tweepy.org/ Tweepy Docs: https://tweepy.readthedocs.io/en/v3.5.0/ Create Twitter Application: https://apps.twitter.com/ GitHub Code for this Video: https://github.com/vprusso/youtube_tutorials/tree/master/twitter_python/part_1_streaming_tweets This video is brought to you by DevMountain, a coding boot camp that offers in-person and online courses in a variety of subjects including web development, iOS development, user experience design, software quality assurance, and salesforce development. DevMountain also includes housing for full-time students. For more information: https://devmountain.com/?utm_source=Lucid%20Programming Do you like the development environment I'm using in this video? It's a customized version of vim that's enhanced for Python development. If you want to see how I set up my vim, I have a series on this here: http://bit.ly/lp_vim If you've found this video helpful and want to stay up-to-date with the latest videos posted on this channel, please subscribe: http://bit.ly/lp_subscribe
Views: 51696 LucidProgramming
K Means Clustering Algorithm | K Means Example in Python | Machine Learning Algorithms | Edureka
 
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** Python Training for Data Science: https://www.edureka.co/python ** This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) series presents another video on "K-Means Clustering Algorithm". Within the video you will learn the concepts of K-Means clustering and its implementation using python. Below are the topics covered in today's session: 1. What is Clustering? 2. Types of Clustering 3. What is K-Means Clustering? 4. How does a K-Means Algorithm works? 5. K-Means Clustering Using Python Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm Subscribe to our channel to get video updates. Hit the subscribe button above. How it Works? 1. This is a 5 Week Instructor led Online Course,40 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 Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Programmatically download and analyze data 2. Learn techniques to deal with different types of data – ordinal, categorical, encoding 3. Learn data visualization 4. Using I python notebooks, master the art of presenting step by step data analysis 5. Gain insight into the 'Roles' played by a Machine Learning Engineer 6. Describe Machine Learning 7. Work with real-time data 8. Learn tools and techniques for predictive modeling 9. Discuss Machine Learning algorithms and their implementation 10. Validate Machine Learning algorithms 11. Explain Time Series and its related concepts 12. Perform Text Mining and Sentimental analysis 13. Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. 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 Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
Views: 53392 edureka!
Mining Twitter with Python : 2 - Collecting data from Twitter
 
39:31
In order to interact with the Twitter APIs, we need a Python client that implements the different calls to the APIs itself. We will use Tweepy in these tutorials and see how to build our application in multiple parts to collects data from our own Twitter timeline and other users timeline. ----- ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 10658 Sukhvinder Singh
Python For Data Analysis | Python Pandas Tutorial | Learn Python | Python Training | Edureka
 
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( Python Training : https://www.edureka.co/python ) This Edureka Python Pandas tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) will help you learn the basics of Pandas. It also includes a use-case, where we will analyse the data containing the percentage of unemployed youth for every country between 2010-2014. This Python Pandas tutorial video helps you to learn following topics: 1. What is Data Analysis? 2. What is Pandas? 3. Pandas Operations 4. Use-case Check out our Python Training Playlist: https://goo.gl/Na1p9G Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #Pythontutorial #Pythononlinetraining #Pythonforbeginners #PythonProgramming #PythonPandas How it Works? 1. This is a 5 Week Instructor led Online Course,40 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 Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. 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: 190925 edureka!
Data Cleaning In Python (Practical Examples)
 
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Data Cleaning In Python with Pandas In this tutorial we will see some practical issues we have when working with data,how to diagnose them and how to solve them. ==Tutorial and Data Set here== Github: https://goo.gl/erg89C Blog: https://goo.gl/6PJsdo Reference ====Common Data Cleaning Issues==== Reading File Inconsistent Column Names Missing Data Duplicates Inconsistent Data Types Outliers Noisy Data etc.
Views: 17223 J-Secur1ty
Predictive Analytics using Orange Data Mining
 
25:41
Data Mining Fruitful and Fun Open source machine learning and data visualization for novice and expert. Interactive data analysis workflows with a large toolbox. Download Link: https://orange.biolab.si/download/
Views: 4595 Anurag P
Big Data Analytics using Python and Apache Spark | Machine Learning Tutorial
 
09:28:18
Apache Spark is the most active Apache project, and it is pushing back Map Reduce. It is fast, general purpose and supports multiple programming languages, data sources and management systems. More and more organizations are adapting Apache Spark to build big data solutions through batch, interactive and stream processing paradigms. The demand for trained professionals in Spark is going through the roof. Being a new technology, there aren't enough training sources to provide easy guidance on building end-to-end solutions. Section 1: Introduction Lecture 1 About the course 08:42 Lecture 2 About V2 Maestros 01:39 Lecture 3 Resource Bundle Article Section 2: Overview Lecture 4 Hadoop Overview 10:06 Lecture 5 HDFS Architecture 14:46 Lecture 6 Map Reduce - How it works 17:24 Lecture 7 Map Reduce - Example 16:46 Lecture 8 Hadoop Stack 06:27 Lecture 9 What is Spark? 14:03 Lecture 10 Spark Architecture - Part 1 13:23 Lecture 11 Spark Architecture - Part 2 13:25 Lecture 12 Installing Spark and Setting up for Python 12:05 Quiz 1 Hadoop and Spark Architecture 5 questions Section 3: Programming with Spark Lecture 13 Spark Transformations 11:33 Lecture 14 Spark Actions 15:04 Lecture 15 Advanced Spark Programming 10:10 Lecture 16 Python - Spark Programming examples 1 16:11 Lecture 17 Python - Spark Programming Examples 2 17:18 Quiz 2 Data Engineering with Spark 5 questions Lecture 18 PRACTICE Exercise : Spark Operations Article Section 4: Spark SQL Lecture 19 Spark SQL Overview 10:03 Lecture 20 Python - Spark SQL Examples 16:16 Quiz 3 Spark SQL 2 questions Lecture 21 PRACTICE Exercise : Spark SQL Article Section 5: Spark Streaming Lecture 22 Streaming with Apache Spark 15:53 Lecture 23 Python - Spark Streaming examples 17:47 Quiz 4 Spark Streaming 3 questions Section 6: Real time Data Science Lecture 24 Basic Elements of Data Science 11:51 Lecture 25 The Dataset 10:44 Lecture 26 Learning from relationships 12:55 Lecture 27 Modeling and Prediction 09:31 Lecture 28 Data Science Use Cases 07:47 Lecture 29 Types of Analytics 12:08 Lecture 30 Types of Learning 17:16 Lecture 31 Doing Data Science in real time with Spark 07:39 Quiz 5 Spark Data Science 5 questions Section 7: Machine Learning with Spark Lecture 32 Spark Machine Learning 12:18 Lecture 33 Analyzing Results and Errors 13:46 Lecture 34 Linear Regression 19:00 Lecture 35 Spark Use Case : Linear Regression 18:33 Lecture 36 Decision Trees 10:42 Lecture 37 Spark Use Case : Decision Trees Classification 14:58 Lecture 38 Principal Component Analysis 07:28 Lecture 39 Random Forests Classification 10:31 Lecture 40 Python Use Case : Random Forests & PCA 13:16 Lecture 41 Text Preprocessing with TF-IDF 14:53 Lecture 42 Naive Bayes Classification 19:21 Lecture 43 Spark Use Case : Naive Bayes & TF-IDF 07:26 Lecture 44 K-Means Clustering 11:53 Lecture 45 Spark Use Case : K-Means 14:26 Lecture 46 Recommendation Engines 11:55 Lecture 47 Spark Use Case : Collaborative Filtering 06:34 Lecture 48 Real Time Twitter Data Sentiment Analysis 10:11 Quiz 6 Spark Machine Learning Algorithms 4 questions Lecture 49 PRACTICE Exercise : Spark Clustering Article Lecture 50 PRACTICE Exercise : Spark Classification Article Section 8: Conclusion Lecture 51 Closing Remarks 01:56 Lecture 52 BONUS Lecture : Other courses you should check out Article
Learn Data Science in 3 Months
 
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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
Data Cleaning Steps and Methods, How to Clean Data for Analysis With Pandas In Python [Example] 🐼
 
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In this Statistics Using Python Tutorial, Learn cleaning Data in Python Using Pandas. learn basic data cleaning steps in excel before importing data in python. We use Pandas Functions to clean data perform exploratory data analysis on our Data set. 🔷🔷🔷🔷🔷🔷🔷🔷 Jupyter Notebooks and Practice Files: https://github.com/theengineeringworld/statistics-using-python 🔷🔷🔷🔷🔷🔷🔷🔷 Data Wrangling With Python Using Pandas, Data Science For Beginners, Statistics Using Python 🐍🐼 https://youtu.be/tqv3sL67sC8 Cleaning Data In Python Using Pandas In Data Mining Example, Statistics With Python For Data Science https://youtu.be/xcKXmXilaSw Cleaning Data In Python For Statistical Analysis Using Pandas, Big Data & Data Science For Beginners https://youtu.be/4own4ojgbnQ Exploratory Data Analysis In Python, Interactive Data Visualization [Course] With Python and Pandas https://youtu.be/VdWfB30QTYI 🔷🔷🔷🔷🔷🔷🔷🔷 *** Complete Python Programming Playlists *** * Python Data Science https://www.youtube.com/watch?v=Uct_EbThV1E&list=PLZ7s-Z1aAtmIbaEj_PtUqkqdmI1k7libK * NumPy Data Science Essential Training with Python 3 https://www.youtube.com/playlist?list=PLZ7s-Z1aAtmIRpnGQGMTvV3AGdDK37d2b * Python 3.6.4 Tutorial can be fund here: https://www.youtube.com/watch?v=D0FrzbmWoys&list=PLZ7s-Z1aAtmKVb0fpKyINNeSbFSNkLTjQ * Python Smart Programming in Jupyter Notebook: https://www.youtube.com/watch?v=FkJI8np1gV8&list=PLZ7s-Z1aAtmIVV0dp08_X-yDGrIlTExd2 * Python Coding Interview: https://www.youtube.com/watch?v=wwtzs7vTG50&list=PLZ7s-Z1aAtmJqtN1A3ydeMk0JoD3Lvt9g
Views: 9144 TheEngineeringWorld
Machine Learning Library (scikit learn) | Python untuk Data Mining Tutorial 2
 
06:48
Python untuk Data Mining | Python for Data Mining Tutorial 2 Data Mining menggunakan bahasa pemrograman Python. Dari Mulai: 1. Alasan Kenapa menggunakan Python 2. Machine Learning Library di Python 3. Komponen bahasa pemrograman Python 4. Virtual environment di Python 5. Dasar-dasar pemrograman Python 6. Numpy, scipy, pandas, matplotlib 7. Data Mining dengan Python 8. Analisis data menggunakan Python 9. Dan sebagainya #Python #DataMining #MachineLearning #DataAnalysis #scikit-learn
Views: 1407 Rischan Mafrur
Python Web Scraping with BeautifulSoup | BS4 data mining
 
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Learn web scraping using the Python Beautiful Soup library. Get HTML web pages using Requests library, and scrape data using BS4. ► Get Jupyter notebook: https://github.com/joeyajames/Python/tree/master/Web%20Data%20Mining ► Subscribe to my Channel https://www.youtube.com/channel/UC4Xt-DUAapAtkfaWWkv4OAw?view_as=subscriber?sub_confirmation=1 ► Thank me on Patreon: https://www.patreon.com/joeyajames
Views: 1239 Joe James
KNN Algorithm using Python | How KNN Algorithm works | Python Data Science Training | Edureka
 
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** Python for Data Science: https://www.edureka.co/python ** This Edureka video on KNN Algorithm will help you to build your base by covering the theoretical, mathematical and implementation part of the KNN algorithm in Python. Topics covered under this video includes: 1. What is KNN Algorithm? 2. Industrial Use case of KNN Algorithm 3. How things are predicted using KNN Algorithm 4. How to choose the value of K? 5. KNN Algorithm Using Python 6. Implementation of KNN Algorithm from scratch Check out our playlist for more videos: http://bit.ly/2taym8X Subscribe to our channel to get video updates. Hit the subscribe button above. #KNNAlgorithm #MachineLearningUsingPython #MachineLearningTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 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 Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. The Machine Learning training will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course, we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience. After completing this Machine Learning Certification Training using Python, you should be able to: Gain insight into the 'Roles' played by a Machine Learning Engineer Automate data analysis using python Describe Machine Learning Work with real-time data Learn tools and techniques for predictive modeling Discuss Machine Learning algorithms and their implementation Validate Machine Learning algorithms Explain Time Series and it’s related concepts Gain expertise to handle business in future, living the present - - - - - - - - - - - - - - - - - - - Why learn Machine Learning with Python? Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning. 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: 64174 edureka!
Lyon Data Science : Place de R et Python dans les formations en Data Science.
 
01:34:32
Session du 19.01.2018 La session portere sur la Place de R et Python dans les formations en Data Science, présentée par Ricco Rakotomalala du Master SISE – Université Lyon 2. La science des données n’échappe pas à la vague des logiciels libres. Depuis plusieurs années, les deux outils les plus populaires auprès des data scientists sont R et Python selon le sondage annuel du site KDnuggets (Mai 2017). Certes, les licences présentent des subtilités un peu difficiles à suivre parfois, mais elles respectent deux caractéristiques fondamentales de mon point de vue : nous avons accès au code source, nous garantissant un certain contrôle sur les calculs et opérations réellement effectuées ; ils sont accessibles et exploitables gratuitement, quels que soient les contextes d’utilisation. De fait, l’adoption de R et Python dans les formations en data science semble évidente. Pourtant, il faut être prudent, ne serait-ce que par principe. Dans mon exposé, je m’appuierai sur ma propre expérience d’enseignant d’une part, de créateur de logiciels de data mining gratuits à vocation pédagogique (SIPINA, TANAGRA) d’autre part, pour essayer de cerner les attentes que l’on peut avoir vis-à-vis des outils dans les cours de statistique et de data science. L’élaboration de TANAGRA (2004) en particulier aura été l’occasion de mener une réflexion approfondie sur les caractéristiques clés que doivent présenter les logiciels pour l’enseignement. Je reviendrai rapidement dessus pour mieux rebondir sur la définition d’un cahier des charges moderne où les compétences en programmation et les accès aux API tiennent une place importante. Dans ce contexte, que l’on pourrait qualifier de Big Data, R et Python se démarquent réellement et justifient pleinement l’investissement que l’on pourrait leur consacrer au sein des formations. Je m’appuierais sur une étude récente réalisée par un groupe d’étudiants du Master SISE pour essayer de cerner les mots clés importants qui caractérisent les annonces dans nos domaines en France. Python y occupe un espace assez singulier.
Views: 6585 Lyon Data Science
Twitter Data Mining using Python | MongoDB with Python | Twitter MongoDB Data Mining
 
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https://gist.github.com/sumitgoyal2006/d10c4d932de3afedd2457dfbdfdadea9
Views: 878 Amit Sharma
Data Mining Preprocessing in Jupyter Notebook with Python
 
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Data Mining Preprocessing in Jupyter Notebook with Python using Pandas, Numpy and a Baseball dataset.
Views: 562 D Thomas
Lecture 12: Business Data Mining (Loan Prediction with Python)
 
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Lecture 12: Business Data Mining (Loan Prediction with Python)
Views: 2401 Phayung Meesad
MSCI 723 Big Data Analytics Tut6: Association Rule Learning, Apriori Algorithm
 
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Hello everyone, this week in the tutorial we covered association rule learning and some apriori algorithm implementations I also introduced Orange, an open source data visualization and data analysis with interactive workflows and a large toolbox. Orange provides a Python library as week as an interface interface for data mining! Orange: http://orange.biolab.si/getting-started/ http://orange.biolab.si/screenshots/ http://orange.biolab.si/docs/latest/widgets/rst/ Tutorial: http://nbviewer.jupyter.org/github/datascienceguide/datascienceguide.github.io/blob/master/tutorials/Association-Rule-Mining.ipynb
Views: 9428 Andrew Andrade
Mining data on Facebook with Python: 2 - Mining our Facebook posts with Python
 
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After setting up our app on Facebook and after getting it to communicate with facebook-sdk we will now start to download our own posts. ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: http://bit.ly/2otJDwn ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 3447 Sukhvinder Singh