Home
Search results “Applications of data mining in real estate”
Mozenda - Data Mining - Real Estate Leads - PT1
 
09:01
http://www.twitter.com/jbmcclelland Justin McClelland (http://www.justinmcclelland.com), provides various how-to demonstrations and example applications of the Mozenda software (http://www.getmozenda.com ). The Mozenda, Software as a Service (SaaS), platform is ideal for performing comprehensive web data gathering (a.k.a web data extraction, screen scraping, web crawling, web harvesting, etc.)
Views: 2965 Justin McClelland
Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
 
24:26
Ian Wong, Co-Founder of Opendoor, spoke at Data Driven NYC on January 24th, 2017. He explained how Opendoor is utilizing data science to value and purchase homes around the country. Data Driven NYC is a monthly event covering Big Data and data-driven products and startups, hosted by Matt Turck, partner at FirstMark Capital.
Views: 7502 Data Driven NYC
Real Estate Data Mining Video
 
05:09
Real Estate Data Mining Video
Find the farm -- data science insights into real estate pricing (en zyme)
 
30:31
Using gmplot, geopy, and Python data science tools we’ll discover realtor farms, and assess the characteristics of sales vs listing price. Real estate transactions tend to be geographically sparse and temporally rare. There is often both a listing and a selling agent in the representing a given property. The sales price is determined by a number of factor. While there has been considerable interest in building pricing models relying on physical parameters, there has been little work done in assessing the contribution of the realtor. The discovery of a ‘farm’ uses cluster identification methods. These farms can then be analyzed for imputed listing prices and the sales price, both of which are negotiated. The problem: Most real estate analytics deal only with property description and location. Markets can swing quickly from buyer’s to seller’s advantage, so timing and days on market is important. Agent effects are not well understood and can be a significant factor in determining the actual price. Data source are examined . Python Modules utilized. Application of data science, e.g. modules pycluster, pyclustering, scikit-learn. (the talk is primarily application, not theory) Examples of geographic and hidden affinity Analysis of listing price to appraisal and listing agent effect Analysis of over/under-performance of sales price to listing price Determination of listing agent vs selling agent negotiation skills. Effect of dual agency on pricing. Effect of listing agent Farms on neighborhood pricing. Consideration as a Machine Learning project using Theano or TensorFlow , Keras, Sonnet tflearn Conclusions and future directions Questions data, code, notebooks, and graphics will be included The methodology presented is likely applicable to other low-volume high-value facilitated transactions. Presentation page -- https://2017.pycon.ca/schedule/65/
Views: 328 PyCon Canada
How to scrape real estate websites ? Real Estate Data Extraction
 
07:26
www.webharvy.com http://www.zillow.com/homes/Walla-Walla-County-WA_rb/1_p/ http://www.zillow.com/homes/Walla-Walla-County-WA_rb/%%pagenumber%%_p/ href="([^"]*)
Views: 9486 sysnucleus
Mozenda - Data Mining - Real Estate Leads - PT2
 
05:55
http://www.twitter.com/jbmcclelland Justin McClelland (http://www.justinmcclelland.com), provides various how-to demonstrations and example applications of the Mozenda software (http://www.getmozenda.com ). The Mozenda, Software as a Service (SaaS), platform is ideal for performing comprehensive web data gathering (a.k.a web data extraction, screen scraping, web crawling, web harvesting, etc.)
Views: 827 Justin McClelland
Real Estate Data Mining, Farming and Farms (part 1 of 2)
 
15:02
Source: https://www.spreaker.com/user/leehonish/real-estate-data-mining-farming-and-farm da·ta min·ing: the practice of examining large databases in order to generate new information. The Farming Game Plan You don't just jump in and start spending money mailing out postcards or refrigerator magnets. Well, maybe you do, but it's not going to be a very good return for your money and time invested. As any corporation would, you need to develop a marketing plan for your farming....
Views: 38 Lee Honish
How to use Import.IO to crawl real estate data from the web
 
15:57
The introduction of the tutorial is available at http://www.louisdorard.com/guest/everyone-can-do-data-science This screencast is the starting point of the series "Everyone can do Data Science". It illustrates how to use Import.IO to crawl the web for real estate data. Here I chose Realtor.com as an example. Part One: http://www.louisdorard.com/guest/everyone-can-do-data-science-importio Part Two: http://www.louisdorard.com/guest/everyone-can-do-data-science-pandas Part Three: http://www.louisdorard.com/guest/everyone-can-do-data-science-bigml
Views: 14823 Fabien Durand
Real Estate Analytics
 
03:14
How Metric-X helps companies that manage Real Estate. We build custom reports, dashboards and analytics solutions for property management. MX39 - 1009
Real Estate Investing -  How to scrape data
 
11:00
On this video, I show the manual process to scrape data. We have automated this process but I am showing you for the sake of making you aware of the possibilities with lots of data.
Views: 71 CuriousMind
Python Web Scraping Real estate website in Lithuania - Aruodas.lt (DEMO)
 
02:44
This is just Data scraping demonstration that was executed by Python. In this Python video I demonstrate the web scraper that I programmed from zero by Python. I scraped one of the most popular real estate website in Lithuania - aruodas.lt. For the first stage of my Web Scraping project I just scraped District and Price of real estate objects (flats for sell) data. Final results are saved to CSV file. BeautifulSoup library was used to execute scraping task in this Python application. The goal of this Python project is to create the biggest database of real estate ads for Data mining and Data visualization purposes. If you need explaining how I executed and prepared it, you can contact me in LinkedIn: https://www.linkedin.com/in/bielinskas/ Vytautas.
Applications of Web Scraping in Cryptocurrency Investment
 
03:28
Check out how web crawling can be applied in cryptocurrency investment - opinion mining, news tracking, price movement and more. --- www.promptcloud.com We specialize in extracting custom, clean and large-volume data from the web.
Views: 1032 PromptCloud
Will Sold Data Change the Real Estate Market
 
02:01
Welcome to Inside the Real Estate Market. I'm Jamie Johnston, Broker/Owner of RE/MAX Condos Plus. So, what's the big deal with making sold data available to the public? For years, good real estate agents supplied their clients with this information in making any real estate transaction. In the US, solds have been available to the public for several years. Now, the Toronto Real Estate Board wants people to view this information through a valid email address and a special website. But now the Canadian Real Estate Association through realtor.ca will now make this information available without any checks. What will be the end result? More sales by FSBO (that's Sale by Owner) Properties? The U.S. experience says no. What does a list of solds provide to owners? Not much. These sales don't tell you what the interiors are really like, or what was next door to the property. For condos, units facing in one direction over another, can mean a difference of $50,000 for the same unit. The real value with good agents is in gathering the right information and interpreting it for their clients. You get stock prices online every day, yet smart people still rely on stock brokers. No more needs to be said.
Views: 36 RE/MAX Condos Plus
Linear Regression Algorithm | Linear Regression in R | Data Science Training | Edureka
 
57:06
( Data Science Training - https://www.edureka.co/data-science ) This Edureka Linear Regression tutorial will help you understand all the basics of linear regression machine learning algorithm along with examples. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial: 1) Introduction to Machine Learning 2) What is Regression? 3) Types of Regression 4) Linear Regression Examples 5) Linear Regression Use Cases 6) Demo in R: Real Estate Use Case Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #LinearRegression #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 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. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies 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 Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 71271 edureka!
Jason Vertrees - Introducing the World of Commercial Real Estate Data to App Developers
 
38:39
PyData Dallas 2015 Much of the $15.2T commercial real estate (CRE) world is closed and clandestine. This has held the industry back from adopting technological progress, creating inefficiencies across the entire ecosystem. With the power of the internet at its side, RealMassive is beginning to break open this industry. One area in which we now shed light is commercial real estate availability data, or CRE supply side data. Application developers can now use our freely open RESTful API to augment their applications or services with CRE data and analytics. In this talk, we explore the API and provide a few examples of the power of being able to access and analyze CRE data.
Views: 396 PyData
CBRE Retail Innovation - Data & Analytics
 
03:32
Learn how retailers are using massive mobile and social media data & analytics to make smarter real estate decisions. Featuring Melina Cordero, Americas Head of Retail Research and Kenna Brannon, VP Technical Sales, Forum Analytics - a CBRE Company.
Views: 2864 CBRE
The Use of Predictive Analytics in Real Estate Investing
 
01:01
Read more about Predictive Analytics in Real Estate Investing: https://www.mashvisor.com/blog/use-predictive-analytics-real-estate-investing Although the term may sound complex, predictive analytics is not a difficult concept to understand. In a nutshell, predictive analytics is the art of analyzing big data by using past data to predict future trends.
Views: 1343 Mashvisor
Commercial Real Estate Data
 
01:50
We also display job growth in our real estate maps and Job growth and local housing market predictions. The Growth Maps number for job growth is an index number, which indicates the latest new job growth, from the Bureau of Labor Statistics and other vendors. http://growth-maps.com/commercial-real-estate-technology-and-job-growth/
Views: 17 growth maps
Real Estate Valuation and Data Analytics Software - iLOOKABOUT Corp.
 
11:01
iLOOKABOUT is a Visual and Data Analytics Company that provides a suite of Software as a Service, supported by Professional Services, focused on the Real Estate and Property Assessment Markets. Presenting in this video is Chief Operating Officer Jordan Ross of iLOOKABOUT (ILA). Join us at an upcoming event! http://www.cambridgehouse.com Be part of our investment community: http://www.cambridgehouse.com/ https://twitter.com/cambridge https://www.facebook.com/cambridgehouseconferences https://www.linkedin.com/company/cambridge-house-international/ Copyright © 2019 Cambridge House International Inc. All rights reserved.
Finding Local Market Data and Real Estate Values in My Area
 
06:54
How to find current market data and trends for your specific area. To get more free training on creatively investing in real estate: http://www.RichardRoop.com/freetrainingsystem In this video Cortney Jones (http://www.facebook.com/cortney.jones) shows you 3 sources that she uses to keep up with local market trends and values. Analyzing your market and watching for trends will help you to see opportunities as they come up. Knowing where to find the information and data and watching real estate values on a regular basis is key.
Views: 1163 TheRichardRoop
Data entry job for real estate application
 
07:42
Seeking anyone who works from home for data entry.
Carrie Little: Leveraging Big Data in Your Real Estate Business
 
03:10
Carrie Little talks about using big data for your real estate business by leveraging tools like RPR and MLS, to get information to create relevant content for social media, digital marketing, and email marketing.
Views: 1415 NAR Meetings
SEO - Keyword discovery tool - Mozenda Data Mining - analyticip.com
 
03:39
http://www.analyticip.com statistical data mining, statistical analysis and data mining, data mining statistics web analytics, web analytics 2.0, web analytics services, open source web analytics, web analytics consulting, , what is data mining, data mining algorithms, data mining concepts, define data mining, data visualization tools, data mining tools, data analysis tools, data collection tools, data analytics tools, data extraction tools, tools for data mining, data scraping tools, list of data mining tools, software data mining, best data mining software, data mining software, data mining softwares, software for data mining, web mining, web usage mining, web content mining, web data mining software, data mining web, data mining applications, applications of data mining, application data mining, open source data mining, open source data mining tools, data mining for business intelligence, business intelligence data mining, business intelligence and data mining, web data extraction, web data extraction software, easy web extract, web data extraction tool, extract web data
Views: 77 Data Analytics
Century 21 Real Estate: Customer Experience with Data and Analytics (CXOtalk #264)
 
42:52
Digital transformation in real estate: Nick Bailey, President and CEO at Century 21, tells CXOTalk how the largest real estate brand in the U.S. navigates changing global trends from data-driven competitors in property listings and homes for sale. He also offers important advice to real estate brokers and agents. For more information: https://www.cxotalk.com/episode/century-21-digital-transformation-real-estate Bailey has more than 21 years of industry experience as a licensed broker, opened a real estate brokerage where he actively listed and sold properties, and previously served as Vice President of Broker Relations for the Zillow Group. He was appointed president and chief executive officer of Century 21 Real Estate LLC in August 2017, leading the iconic C21 brand and its approximately 7,450 independently owned and operated offices in 79 countries and territories worldwide. From the transcript: Michael Krigsman: Nick, tell us about Century 21. Nick Bailey: Well, you said it best. An iconic brand around the globe, this is an organization that has been a world leader in real estate, spanning nearly 80 countries, nearly 7,500 locations, and 115,000 sales professionals worldwide that are helping buyers and sellers every single day. This is an organization that, over its 46 years in existence, has grown to [be] know [as] the best brand between buyers and sellers on the entire planet. Michael Krigsman: Now, real estate is undergoing tremendous change. Maybe you can set the stage for us by describing what's going on in the market that's shaping real estate today. Nick Bailey: There is a lot of talk about what's changing in real estate. I think it comes down to one thing, which is, we are in a consumer-driven movement. What I mean by that, it's not just specific to real estate, but it's also just how consumers are engaging with products and services. We can point to many companies that have been at the forefront of this movement, companies like Amazon, like Netflix, like Uber. Via the mediums of technology, consumers are able to make things easier, faster, or take anxiety out of the process. How that translates to real estate today is, the home search process is very popular. People jump online. They jump on their mobile device looking for property, dreaming about property in certain vacation areas, and they get very involved. Real estate is a hot topic. Look at television shows about remodeling your home, or should I stay in it or buy something else? It's just something that's become at the forefront of consumers and excitement. With that, though, comes a great deal of opportunity, which is, if anyone has bought or sold real estate lately, they know that the home search part of it can be fun and exciting. But as soon as you go into the next steps of the home shopping and going into actually purchasing a property, the process of how you go from purchasing that property to moving into it has a lot of room to be improved. Unfortunately, you ask many people that have bought a home recently if they'd like to do it again soon and, generally, they say no because the process to get there is so complex. That's where having a real estate professional to help with that process is crucial. Michael Krigsman: The consumer experience dimension, can we say that's your special sauce, or is that your focus? How would you characterize that? Nick Bailey: As you mentioned, with a lot of change that's going on in the industry from what does home search mean, how do consumers engage with their real estate professional, and how do all those components come together, here's what I know. The real estate professional is still the most important part of a real estate transaction for someone wanting to buy or sell. There is no level of data or analytics that can do the job of what a knowledgeable professional can do to help someone make what is generally the biggest financial decision of their life. It's still very emotional. If you look at all the data and analytics behind price depreciation and comparables within a neighborhood, still you walk into a home and it's a very emotional process of, do I want to live here; do I want to raise my family here? Here's where the memories and the holidays take place. There's a balance between that emotional need and then the financial analytical side. When we look at it as an organization, we have to balance both of them, which we're dealing, at Century 21, with entrepreneurs that want to build their business and help people buy and sell. We're also dealing with consumers that are buying and selling and saying, "I am demanding a better process." We have to, as leaders, be able to bring those two constituents together to create a better result for both.
Views: 5489 CXOTALK
Drivetrain - Data Mining in Used Car Data - UNR CS 426 Senior Project 2018
 
03:39
Project video of the Android app developed as part of the Computer Science senior projects at the University of Nevada, Reno, 2017/2018. Project website: https://cs426team8.github.io/Drive-Train/
Views: 125 Mile Cilic
Data Mining Online Job Ads and Applications - Macalester College Capstone Talk (4/12/17)
 
16:11
“Data mining” – or, when dealing with the Internet, “web scraping” – is the process of harvesting usable data from an unstructured data source. This capstone talk deals with work conducted at the Minnesota Department of Employment and Economic Development (DEED) that involves data mining online job ads. Applications of the constantly growing dataset, which currently contains over 5 million ads, include automated collection of workforce data and modeling with machine learning algorithms.
Views: 70 Nick Michalesko
Learn Web Scraping, Data Mining Course , Lecture 01
 
03:06
Download Any web scraper from https://webscrapingtools.net/ Ultimate Extractor for Every Task Whenever you need to extract some typical data from multiple web pages, Web Content Extractor is the ultimate solution. Extract product pricing data, grab real estate data; parse Forex and stock market figures; extract book, song or movie information; gather news and articles on a certain topic; extract web content on hotels or car rentals in a given country; collect information from dating sites or job web-resources - this is merely a short list of Web Content Extractor possible applications. Of course, you are not limited with the above; the tool perfectly works with any kind of web information and thanks to fine customization it can deal with any website whatsoever. Powerful Web Crawler Engine Inside Powerful, multi-threaded web crawler engine provides for quick and efficient data extraction. Web Content Extractor supports password protected websites and can access the Internet via multiple proxy-servers ensuring speed and reliability. Not only does the crawler support downloading with up to 20 simultaneous threads, it is also highly configurable. You can set it to ignore certain URLs or include them into the extraction basing on a title or a URL match. Such flexibility means accurate web scraping at high pace, as well as is an additional way to customize the process. Wide Exporting Capabilities In addition to its immerse extracting power, the program also features wide exporting capabilities. You can save gathered data into a plain CSV or text file, export to HTML or XML, as well as to put the data right into a given database format using the built-in possibility to export information into MSSQL/MySQL script or directly into any ODBC-compatible destination. This allows you to apply the scraped data immediately - say, perform an in-depth analysis using spreadsheet application, create a summary report and upload it via FTP, or import the data into your own application or service's database. Enjoy Automation! Web Content Extractor provides serious automation of the website scraping task. Usually, you only need to specify a basic extraction pattern (done in few clicks too) and run the extraction process. The program automatically scans the provided URLs and scrapes all the info that meets the specified template. And command line options allow to set the program to work with any third-party scheduler. The program doesn't try to outsmart a user though. Yes, it determines elements on a page and the type of the data field suggesting the extraction results as a preview, but you can always make necessary changes or adjust the program's choice manually if needed. Reliable, highly automated, powerful web scraping software Web Content Extractor is certainly a tool you need if your business is somehow related to web data extraction. Being a huge time-saver, this tool has probably the best value for money, plus you can try it for free! Download the free evaluation version now!
Views: 27 WebScrapingTools
What is the best commercial real estate data source?
 
01:26
Appreciate the video? The best thank you is to check out our sponsors. See if they might be of value to you, or your referrals. http://commercialrealestateshow.com/c... Don’t miss a show of special interest to you, subscribe to our weekly show topic email notification. You’ll know who’s on the show and what it’s about. http://bit.ly/2gfoKSN You’re invited to subscribe to the show’s YouTube channel. http://www.youtube.com/subscription_c... For more videos, podcasts, and articles, visit http://www.CREshow.com
How Predictive Modeling Works
 
08:07
How Predictive Modeling Works for Real Estate Investors and local wholesellers.
Views: 1411 Audantic
IoT Big Data Stream Mining (Part 3)
 
45:27
Authors: Latifur Khan, Department of Computer Science, Erik Jonsson School of Engineering & Computer Science, The University of Texas at Dallas João Gama, Laboratory of Artificial Intelligence and Decision Support, University of Porto Albert Bifet, Telecom ParisTech Abstract: The challenge of deriving insights from the Internet of Things (IoT) has been recognized as one of the most exciting and key opportunities for both academia and industry. Advanced analysis of big data streams from sensors and devices is bound to become a key area of data mining research as the number of applications requiring such processing increases. Dealing with the evolution over time of such data streams, i.e., with concepts that drift or change completely, is one of the core issues in IoT stream mining. This tutorial is a gentle introduction to mining IoT big data streams. The first part introduces data stream learners for classification, regression, clustering, and frequent pattern mining. The second part deals with scalability issues inherent in IoT applications, and discusses how to mine data streams on distributed engines such as Spark, Flink, Storm, and Samza. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 267 KDD2016 video
Blockchain tutorial 24: Blockchain and miners
 
07:34
This is part 24 of the Blockchain tutorial explaining what a Blockchain is and what miners are. This tutorial explains the following: - what the blocks are in the blockchain - what data does a block contains - what a block number and block height is - what a genesis block is - what a main chain, side fork or orphaned forks are - what miners are and their purpose - what a coinbase transaction is and how Bitcoins are created - there will be maximum 21 million Bitcoins - what a block reward is - what block reward halving is - what a hash puzzle is In this video series different topics will be explained which will help you to understand blockchain. Bitcoin released as open source software in 2009 is a cryptocurrency invented by Satoshi Nakamoto (unidentified person or group of persons). After the introduction of Bitcoin many Bitcoin alternatives were created. These alternate cryptocurrencies are called Altcoins (Litecoin, Dodgecoin etc). Bitcoin's underlying technology is called Blockchain. The Blockchain is a distributed decentralized incorruptible database (ledger) that records blocks of digital information. Each block contains a timestamp and a link to a previous block. Soon people realises that there many other use cases where the Blockchain technology can be applied and not just as a cryptocurrency application. New Blockchain platforms were created based on the Blockchain technology, one of which is called Ethereum. Ethereum focuses on running programming code, called smart contracts, on any decentralized application. Using the new Blockchain platforms, Blockchain technology can be used in supply chain management, healthcare, real estate, identity management, voting, internet of things, etcetera, just to name a few. Today there is a growing interest in Blockchain not only in the financial sector but also in other sectors. Explaining how Blockchain works is not easy and for many the Blockchain technology remains an elusive concept. This video series tries to explain Blockchain to a large audience but from the bottom up. Keywords often used in Blockchain conversation will be explained. Each Blockchain video is short and to the point. It is recommended to watch each video sequentially as I may refer to certain Blockchain topics explained earlier. Check out all my other Blockchain tutorial videos https://goo.gl/aMTFHU Subscribe to my YouTube channel https://goo.gl/61NFzK The presentation used in this video tutorial can be found at: http://www.mobilefish.com/developer/blockchain/blockchain_quickguide_tutorial.html #mobilefish #blockchain #bitcoin #cryptocurrency #ethereum
Views: 12511 Mobilefish.com
Unlocking Value in Customer Data to Drive Growth and Real Estate Strategy
 
44:27
Let Pitney Bowes Software and Dave Bolan, Director of Analytics, Rexall Canada, share with you the five not-so-common best practices for unlocking the maximum analytic power from your data. It all begins with leveraging data for powerful visualizations and reporting, thereby facilitating the creation of actionable information.
Views: 148 Pitney Bowes
Real Estate Data - Presentation
 
02:57
Published as an example of Excel and PowerPoint data analysis and presentation.
Views: 137 Dan Morris
ESRI on Geographical Information Systems (GIS) for the Commercial Real Estate Industry
 
11:35
http://www.CREPIG.com ESRI on Geographical Information Systems (GIS) for the Commercial Real Estate Industry Simon Thompson, Director, Commercial Solutions for ESRI, explains the uses of GIS for CRE at the 2011 National Association of Realtors (NAR) Conference in Anaheim, CA.
Views: 2085 JW Najarian
What's Up With National Housing Data, Anyway - Today's Mortgage & Real Estate News - Growella
 
02:05
The FHFA says home prices are up, but that data doesn't matter much to home buyers today; Mortgage rates holding near multi-week highs; and, home buyers are getting approved with credit scores in the 500s. MORTGAGE LOAN OPTIONS FOR YOU --- https://growella.com/waterstone/mortgage-rates-and-help/ More on mortgages at https://growella.com/mortgage/ Subscribe to Growella: https://www.youtube.com/channel/UCmVzrkCIKVn-yLK5MpdRnLA?sub_confirmation=1 Growella ON YOUTUBE Subscribe to Growella: https://www.youtube.com/channel/UCmVzrkCIKVn-yLK5MpdRnLA?sub_confirmation=1 Playlist for Mortgage News: https://www.youtube.com/playlist?list=PLE-u2lA9xk1iLkG_GRBubKv9DBtJzz5Sk FOLLOW Growella Instagram: https://www.instagram.com/growella/ Facebook: https://facebook.com/growella Twitter: https://twitter.com/growella Grow your money. Grow your life. Growella. Learn More about Growella: https://growella.com/about/
Views: 1693 Growella
Mozenda - Data Mining - Web Crawler - CatalogExample
 
03:07
http://www.twitter.com/jbmcclelland Justin McClelland (http://www.justinmcclelland.com), provides various how-to demonstrations and example applications of the Mozenda software (http://www.getmozenda.com ). The Mozenda, Software as a Service (SaaS), platform is ideal for performing comprehensive web data gathering (a.k.a web data extraction, screen scraping, web crawling, web harvesting, etc.)
Views: 803 Justin McClelland
Mozenda - Data Mining - Web Crawler  - ConsumerResearchExample
 
05:27
http://www.twitter.com/jbmcclelland Justin McClelland (http://www.justinmcclelland.com), provides various how-to demonstrations and example applications of the Mozenda software (http://www.getmozenda.com ). The Mozenda, Software as a Service (SaaS), platform is ideal for performing comprehensive web data gathering (a.k.a web data extraction, screen scraping, web crawling, web harvesting, etc.)
Views: 1037 Justin McClelland
Mozenda - Data Mining - Web Crawler - EntertainmentResearchExample
 
04:32
http://www.twitter.com/jbmcclelland Justin McClelland (http://www.justinmcclelland.com), provides various how-to demonstrations and example applications of the Mozenda software (http://www.getmozenda.com ). The Mozenda, Software as a Service (SaaS), platform is ideal for performing comprehensive web data gathering (a.k.a web data extraction, screen scraping, web crawling, web harvesting, etc.)
Views: 1065 Justin McClelland
Capture Data from Website to generate more leads - Real Estate Agent Website
 
06:36
See on Capture more date from Website and mobile applications to generate more leads with smart website. Get a smart website by ibiixo! Web : www.ibiixo.com email : [email protected] Phone : +91 281 222 0 111
Scrape Real Estate Data: (Example: www.realtor.com)
 
04:19
Welcome to Octoparse tutorial. In this video, I’m going to show you how to access real estate data from www. Realtor. com, which is an online real estate agent in the US. As a real estate agent, you might need to gather information for yourself. If you like this video, please thumb up and subscribe our channel! ( For more information please check out www.octoparse.com.)
Views: 7595 Octoparse
Albert Saiz: Insights for Industry - The Big Data Revolution in Real Estate
 
03:41
MIT Center for Real Estate Director Professor Albert Saiz discusses Insights for Industry - The Big Data Revolution in Real Estate RELATED STORY: http://ilp.mit.edu/newsstory.jsp?id=20315
Examples Where Web Scraping Is Used - Aitomation
 
01:45
There are many real business examples for which web scraping is being currently used by businesses. The following are some examples. Real Estate Listings gathering – It is a huge and growing web scraping area. This is an area where the businesses are using web scraping to gather already listed properties. Who is using it : All MLS companies are using it. Many Real Estate Agents are using it as well. (Although for very specific websites) 2. Email Address gathering – This is used by a lot of companies. The main purpose of this is lead generation. Once the emails are collected, bulk emails are sent. Who is using it: Many different businesses usually practicing email marketing 3. Product review scrapes – this is an important one and the reason why many companies use it is so that they can keep an eye on their competitors. Who is using it: Usually companies selling specific products (they scrape competitors website) 4. Scraping to create other websites. The purpose is to get similar data from different websites and then post all that data into one. Who is using it: Website creators. You might have heard of a scraper website. A good example would be indeed, a specific website example would be 10bestquotes.com 5. Collecting data from different social media websites, whats trending and whats in. Who uses it : A lot of social media companies. 6. Getting massive amounts of data for research purposes. This could be scraping of government websites or other websites for stats, general information and such. Who uses it: Research Companies (This is again a growing one) Research companies pull in massive amounts of data and then make sense of it. 7. Specific task scraping / One time scraping. This is when you need data from a particular website for a very specific purpose just one time. Who uses it: Almost all businesses. Example : Scraping of funny video titles with more than 1 million views. To analyze what kind of titles are doing well. Scraping Amazon for specific category of books. Scraping reddit for particular keywords to get all the info about it. Like when and why are people using that keyword. So on. For further info, please contact on any of the following : Contact at : [email protected] Website : http://aitomation.com/ Facebook : https://www.facebook.com/Aitomation/ Twitter : https://twitter.com/Aitomation1 LinkedIn : https://www.linkedin.com/company/aitomation Youtube : https://www.youtube.com/c/AitomationAI Instagram : https://www.instagram.com/aitomationai/ Tumblr : https://www.tumblr.com/blog/aitomation Google+ : https://plus.google.com/+AitomationLtd Pinterest : https://www.pinterest.com/aitomation/ Scoop it : http://www.scoop.it/u/aitomation Delicious : http://del.icio.us/aitomation Diigo : https://www.diigo.com/profile/aitomation SmugMug : https://aitomation.smugmug.com/ Vimeo : https://vimeo.com/aitomation Dailymotion: http://www.dailymotion.com/aitomation
Views: 779 Aitomation