Search results “Applications of data mining in real estate”
Mozenda - Data Mining - Real Estate Leads - PT1
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: 2849 Justin McClelland
BIG Data and Hadoop Applications in Real Estate
Register here for FREE ACCESS to our BIG Data & Hadoop Training Platform: http://promo.skillspeed.com/big-data-hadoop-developer-certification-course/ This is a short video presentation on Applications of Big Data & Hadoop in Real Estate. BIG Data & Hadoop in Real Estate industry is revolutionizing how builders construct infrastructure, while creating new experiences for it's consumers. Real Estate use Big Data analytics for accurate management of large scale projects, smart searches vial lifestyle scores & trends, detecting ideal zones for development and building intelligent homes. The agenda of the session is as follows ✓ Introduction to BIG Data & Hadoop ✓ BIG Data & Hadoop Use Cases in Retail ✓ Examples – Liberty Building Forensics Group & Housing.com ✓ Deriving Insights from BIG Data ---------- What is BIG Data & Hadoop? Big Data refers to the vast amounts of unstructured data generated in today’s internet driven world which cannot be tapped, manipulated and utilized via traditional data harness tools. Apache Hadoop is an open-source JAVA based framework, which is used to harness & process BIG Data sets. It facilitates distributed parallel processing via cluster nodes to ensure a secure, scalabe & accurate data service solution. The framework consists of Hadoop Distributed File System (HDFS), Hive, Sqoop, Flume, Hbase, Pig, Yarn & ZooKeeper. This video will decipher Big Data in Real Estate& Hadoop in Real Estate. ---------- Examples of BIG Data & Hadoop in Real Estate Liberty Building Forensics Group They’ve utilized BIG Data for the construction optimization of 500+ projects worldwide, including a Walt Disney Project. Delays & operational hassles often occur on large-scale construction projects, these can result in budget spirals. LBFG tracks the performance & competency of labor, equipment, materials and deadlines to ensure that the project wraps up without any delays or hassles. Housing.com They’re the first real estate portal in India to provide price-demand heat-maps, lifestyle ratings for areas, demand supply maps and predictions on property prices in the near future. All this is powered by BIG Data. ---------- Skillspeed is a live e-learning company focusing on high-technology courses. We provide live instructor led training in BIG Data & Hadoop featuring Realtime Projects, 24/7 Lifetime Support & 100% Placement Assistance. Email: [email protected] Website: https://www.skillspeed.com Number: +91-90660-20904 Facebook: https://www.facebook.com/SkillspeedOnline Linkedin: https://www.linkedin.com/company/skillspeed
Views: 1942 Skillspeed
Real Estate Data Mining Video
Real Estate Data Mining Video
How Real Estate Agents Tap Big Data
To target prospective clients in competitive markets, tech-savvy agents are teaming up with firms that identify potential buyers using increasingly precise metrics. WSJ's Stefanos Chen reports. Photo: Jason Henry for The Wall Street Journal Don’t miss a WSJ video, subscribe here: http://bit.ly/14Q81Xy More from the Wall Street Journal: Visit WSJ.com: http://www.wsj.com Visit the WSJ Video Center: https://wsj.com/video On Facebook: https://www.facebook.com/pg/wsj/videos/ On Twitter: https://twitter.com/WSJ On Snapchat: https://on.wsj.com/2ratjSM
Views: 2575 Wall Street Journal
Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
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: 6462 Data Driven NYC
Mozenda - Data Mining - Real Estate Leads - PT2
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: 807 Justin McClelland
Find the farm -- data science insights into real estate pricing (en zyme)
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: 184 PyCon Canada
Blockchain Applications Helps Real Estate Companies in Ghana Bitland 2016
Blockchain Applications Helps Real Estate Companies in Ghana Bitland 2016 http://bitlandglobal.com Blockchain Cadastr Ghana | blockchain applications (bitcoin, ethereum) are a form of smart secure technology application. Blockchains uses code and is even used social, in workshops and by microsoft contracts. | WANT TO INVEST IN GHANA !? THAN MAKE SURE YOUR LAND TITLE IS PROPERLY PROTECTED USING OUR SERVICES THEREFOR THE BLOCKCHAIN WHAT IS BLOCKCHAIN ? A block chain or blockchain is a distributed database, introduced in Bitcoin, that maintains a continuously-growing list of data records that each refer to previous items on this list and is thus hardened against tampering and revision. The initial and most widely known application of block chain technology is the public ledger of transactions for bitcoin, which has been the inspiration for other cryptocurrencies and distributed database designs. TRUSTED TIMESTAMP The bitcoin block chain can be used as a trusted timestamp for arbitrary messages. Third party application services store messages directly in the block chain, allowing anyone who has the block chain to read the message WHO SHOULD CONTACT BITLAND !? Bitland is currently offering services to citizens of Ghana as well as companies and farm unions in Ghana - Bitland will investigate the land title that was issued by the land commission of Ghana - then survey the land (as land surveyor in Ghana) - talk to nearby neighbours (to confirm the land-title validity by mouth). - Record the GPS coordinates with a GPS device - Write down the GPS coordinates of the property - Back in the office will submit the data and information to the Blockchain computer registry - Finally Bitland will send a paper-copy of the submitted records to the customer and rightful property owner (as a certificate). BITLAND AND THE GHANA LAND COMMISSION The Bitland Land Registry Procedure is done in addition to the Land Commission procedure. Bitland creates an extra record (elsewhere) that acts as a benchmark. This record is stored in a blockchain meaning that it is super secure and impossible to forge or tamper with (even by Bitland). You could say that it becomes “written in stone”. Should later on a legal land dispute arise then this conflict can be settled (outside of court) quick and easy (meaning with low costs such as the cost of sending a fax with a fax machine to fax the Bitland Certificate). BITLAND INVESTOR RELATIONSHIPS Bitland provides the best services to property investors in Ghana and foreign investment. Bitland can (also) help property investors each step of the way to secure land title registration as well as finding properties to invest in .. We also investors in properties in our portfolio. Bitland has the contacts, the network, the web presence, the know how and good intentions. Bitland is connected to dozens of farm unions so for those interested in gold mining, cacao farming or housing then contact Bitland as well. Note that Bitland values her integrity and besides is aware that maintaining a good reputation can only fulfill our long term global aspirations. We work and worked closely with the Ghana Land Commission Office. BITLAND GLOBAL Bitland is currently (also) developing a Global Blockchain Cadastral System so the Bitcoin-Blockchain Technology can be offered on a large scale .. for example all African nations. Bitland’s efforts will likely (also) uncover vast amounts of money in unknown real estate rights. CALL: +233246255577 EMAIL: [email protected] PERSON: mr. Narigamba Mwinsuubo FACEBOOK: http://www.facebook.com/narigamba FACEBOOK PAGE: https://www.facebook.com/realestatela... GOOGLE+: https://plus.google.com/u/0/109196501... GOOGLE COLLECTION: https://plus.google.com/u/0/collectio... TWITTER: https://twitter.com/realestateghana YOUTUBE: https://www.youtube.com/watch?v=d5cpe... CHANNEL: https://www.youtube.com/channel/UCM-m... REAL ESTATE: https://www.youtube.com/watch?v=MnJKI... FORUM: https://youtu.be/tla6_T1Yt40 #GHANA #REALESTATE #BITLAND #BLOCKCHAIN#LEGAL #ARCHITECTS #GOLDMINING #CACOA #CACAO #FARMERS #WondaWorld #LANDREGISTRATION #LANDGHANA VISIT: http://bitlandglobal.com
Using Data Mining in Forecasting Problems
In this presentation, Analytics 2012 keynote speaker, Tim Rey from Dow Chemical Company, shares methodologies for using data mining to get the most value out of time series data.
Views: 8782 SAS Software
Real Estate Data Mining, Farming and Farms (part 1 of 2)
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: 31 Lee Honish
Things You Need to Know about Real Estate & Big Data Integration
By itself and without context, Big Data has little or no value. Now, more than a Googolplex of Data is available for analysis. But what will we do with all of that data? The collection of data is still meaningless unless ......... To read my full post in addition to the video, click on the following link http://tinyurl.com/lq7y5ll
Views: 247 CRE Radio
Jason Vertrees - Introducing the World of Commercial Real Estate Data to App Developers
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: 379 PyData
Century 21 Real Estate: Customer Experience with Data and Analytics (CXOtalk #264)
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: 5311 CXOTALK
Python Web Scraping Real estate website in Lithuania - Aruodas.lt (DEMO)
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.
Views: 501 Vytautas Bielinskas
Web Scraping, Screen Scraping, Web Data Mining, Data Extractor
Input FORMAT SUPPORT [website, webpage, Text, pdf, CSV, database] Output FORMAT SUPPORT [ excel, csv, tsv, pdf, xml, html, sql, MySql ] » Hotel website [ hotel name, address, images, reviews, latitude-longitude, price ] Scraping » Hotel price scraping for marketing intelligence [againast to your competitor] » Real Estate Data Extraction » Extract Store Details » University's Web Data Scraping » Extract Product Description » Web Information Extractor » Craigslist Email Extractor » Metadata Extraction » Website Email Extraction » Scraping Business Directory » Yellow Pages Scraping » PriceGrabber Data Extraction » Scraping Property Information » Amazon Product Extraction » Download Product Images » Automate osCommerce Product Upload » Scraping Business Contact » Craigslist Posting Service » Imdb Data Extraction » Meta Data Extraction » Scraping From Dynamic Pages » Extract Lyrics Data » Email Scraping & Extraction » Scraping Customer List » Scraping Data From WebSite ----------------------------------- Expertise In -------------------------- » Hotel Website Scraping [expedia.com, hotels.com, booking.com, orbitz.com, airasia.com, easybook.com, laterooms.com, travelocity.com, thomascook.com, activehotels.com, priceline.com, lastminute.com, yatra.com, makemytrip.com etc.] » Ads Classifieds Scraping [gumtree.com, olx.com, craigslist.com etc] » Real Estate Scraping [99acres.com, www.zillow.com, www.trulia.com, www.realtor.com, www.agentimage.com, www.realtysoft.com, www.realestate.com.au etc.] » Product catalog Scraping [amazon.com , ebay.com, yellowpage, whitepage etc.] Contact if any service require [ [email protected] ]
Views: 61866 vickyrathee2005
Spatial Data Mining I: Essentials of Cluster Analysis
Whenever we look at a map, it is natural for us to organize, group, differentiate, and cluster what we see to help us make better sense of it. This session will explore the powerful Spatial Statistics techniques designed to do just that: Hot Spot Analysis and Cluster and Outlier Analysis. We will demonstrate how these techniques work and how they can be used to identify significant patterns in our data. We will explore the different questions that each tool can answer, best practices for running the tools, and strategies for interpreting and sharing results. This comprehensive introduction to cluster analysis will prepare you with the knowledge necessary to turn your spatial data into useful information for better decision making.
Views: 21487 Esri Events
GM's Latest Investments and How The Real Estate Industry Utilizes Big Data; 5/15/15 WSPD
www.TreeceInvestments.com Friday morning Dock and Fred discuss Thursday's economic reports, GM's billion dollar plan to invest in the Warren Tech Center, realtors using big data to attract new clients, positive signs in the local residential real estate market and much more. http://www.wsj.com/articles/how-real-estate-uses-big-data-to-track-clients-1431615728 [email protected] 419 843 7744 800 624 5597 @TreeceInvest http://www.facebook.com/pages/Treece-Investment-Advisory-Corp/153193594714351 The above information is the express opinion of Dock Treece and should not be construed as investment advice or used without outside verification.
Views: 28 TreeceInvestments
Real Estate Data - Presentation
Published as an example of Excel and PowerPoint data analysis and presentation.
Views: 131 Dan Morris
Complete Data Web - Real Estate Software
CD-WEB leverages off the PHP Web Publishing that we can build into your existing server system. PHP is the most popular programming language used to create data-driven websites. When combined with PHP Web Publishing, CD-WEB lets you access your core Complete Data information from any mobile web browser. For example, you can find a Contact, view their buyer requirements and notes or enter Inspections for a Listing using a mobile web application optimised for your mobile device. The system is live and not reliant on synchronisation.
Views: 1411 Robyn McCaughan
Finding Local Market Data and Real Estate Values in My Area
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: 1089 TheRichardRoop
Examples Where Web Scraping Is Used - Aitomation
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: 703 Aitomation
Linear Regression Algorithm | Linear Regression in R | Data Science Training | Edureka
( 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 Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. 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: 60025 edureka!
Equity Mining Calls for Auto Dealership BDC
Here is a simple role play call that you can use when data mining your customer base.
Views: 1214 Jason Parman
Roost Social Real Estate Application for Facebook Setup
We take you through the configuration process of the Roost Social Real Estate Application for Facebook.
Views: 1652 Roostdotcom
Data Mining Services West Palm Beach Florida
Data management is an invaluable resource that businesses are not taking advantage of. Many companies aren’t aware that there’s a science behind the collection, transformation, and application of data to create business strategies and solutions. This process is called data mining, and it isn’t exactly a walk in a park. Data mining is an in-depth, highly involved, and incredibly time-consuming process that many companies just can’t execute in-house.
Views: 7533 Michael Fieger
Power Tools for Commercial Real Estate
Intuition and luck alone won't help you get ahead in commercial real estate. Successful firms make every moment count. By embracing Esri technology they reduce the time between analysis and sharing, so they can spend less time behind computers and more time with clients. Using tools like Smart Map Search, real estate professionals are discovering viable markets around the country in seconds, not days - and you can too. www.esri.com/industries/real-estate
Views: 685 Esri Industries
Mozenda - Data Mining - Web Crawler - SimpleReplacements
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: 1078 Justin McClelland
[Lecture 9] Enterprise Blockchain: Real-World Applications
Blockchain Fundamentals Lecture 9 -- Nadir Akhtar
Data Mining Company In India
http://www.labdhie.com/ - Labdhie Support Services is the go-to company for all your data mining or research needs. Watch the demo. Be it internet research, data collection, real estate MLS, linkedin research or even blog search, we do it all.
Views: 469 Labdhie
Albert Saiz: Insights for Industry - The Big Data Revolution in Real Estate
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
Website listing real estate transaction data to open
A new website listing real estate transaction info opens tomorrow. Prospective buyers and sellers can use the website to see valuable information related to property sales in their area. Bookkeeping for real estate transactions has increased dramatically recently. Deals must be keyed into a website established by the Ministry of the Interior. To meet the new requirements, land administration agencies have had to hire new personnel.Hsiao Chao-yangLand Administration AgentWe had to increase our staff by 10 percent which led to additional costs. Also there are too many sales forms.After two and a half months of registering and collating data, tomorrow the website opens for business. Users choose the information they want to see, including sale prices, rent or presale prices. They then enter t
Views: 70 民視綜合頻道
Mozenda - Data Mining - Web Crawler - HealthCareExample
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: 396 Justin McClelland
SEO - Keyword discovery tool - Mozenda Data Mining - analyticip.com
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: 72 Data Analytics
Scraping Real Estate - Real Estate Data Extraction
Visit this website:http://cyma-accounting-software.com
Views: 55 WebHarvyCrack04
Drones Applications (Construction, Architecture, Surveying, GIS, Mining) [PEEK DRONES]
Our unique combination of UAV Drones and Cloud Data bring new possibilities to the construction, architecture, surveying, mining industries. If you have any questions about what drones can do for your project get in touch - [email protected]
Views: 35795 Peek Drones
Big data and mining panel - 2018 Progressive Mine Forum
A panel of experts discusses applications for big data in mining. This was recorded at the 2018 Progressive Mine Forum in Toronto, presented by The Northern Miner and Canadian Mining Journal. Moderator: John Cumming, The Northern Miner editor-in-chief. Panellists (from left): Talia Dabby, PwC Canada director; Glenn Mullan, PDAC president; Humera Malik, Canvas Analytics CEO; Gordon Stothart, Iamgold executive vice-president and chief operating officer; and Shelby Yee, RockMass Technologies co-founder and CEO.
Views: 121 The Northern Miner
Australian Property Downturn 2018
Australian house prices have been in the news again, and not for the right reasons. Experts warn that due to factors such as unemployment, underemployment, lacklustre wage growth, weak house prices, and the looming threat of interest rate rises, mortgage stress is set to surge. Rates of mortgage default are highest in the mining states of Western Australian and Queensland. 15 of the top 20 worst performing suburbs are in these two states. Credit ratings agency Moody’s suggests that the situation will only get worse as more and more interest-only loans are converted to principal and interest loans over the next 12 months. The Australian dream of owning your own home is looking less and less likely for a growing number of Australians. Martin North, of Digital Finance Analytics, makes a comparison with the current state of the Australian housing market with that of Ireland in 2007 just as its property market started to crash. All current metrics indicate that Australia is in a massive property bubble — metrics such as high debt-to-income and price-to-rent ratios. Australia currently has very low mortgage interest rates, and up until recently, very loose lending policies, which ultimately encouraged speculative buying. Many newly constructed apartments are simply not selling. A lot of property developers are now in financial difficulty. Interest rates can’t get any lower, so only have one direction they can go — up. The number of interest-only loans in Australia is staggering. Over the next few years, a total of about $360 billion of interest-only loans will roll over to interest plus principal, which equates to higher repayments for borrowers. We’re setting ourselves up for one massive fall. Although, the Reserve Bank of Australia may not increase domestic rates any time soon, the big Australian banks all borrow offshore. The US, for example, has raised its rates eight times in the last few years. Australian banks will be forced to raise their mortgage rates regardless of the RBA’s movements — and that’s exactly what we have seen over the last month or two. Currently, there are also quite low rental yields. That is, properties are relatively expensive to buy compared to renting them. This is often a sign that the market is overvalued. If people cannot afford to buy the house they are currently renting, then something is askew. Sydney University economics professor Colm Harmon stated that this situation cannot persist long-term without something giving way. About 40% of first-home buyers are unable to get finance due to recent restrictions imposed by Australia’s regulators. If you go back two or three years, almost everybody could get a loan. Australians are now one of the most indebted people in the world at about 200% of household income. Last week, Sydney house prices fell for the 12th consecutive month. Is this the beginning of a slow deflation, or a gigantic burst? Many forecasters predict a reduction of 10% as a “base case”. What if the declining prices result in a sudden halt to the housing construction boom? Then of course, lots of people will lose their jobs increasing the number of housing loan defaults. This will lead to forced sales adding more pressure on an already struggling market. In this sort of situation, many people will be left with debts greater than the value of their property. Homeowners typically will do anything to keep a roof over their heads, but investors are more likely to sell when they see signs of a downturn in order to minimise their losses. Some companies are already preparing themselves for a property crash. AustralianSuper, Australia’s largest superannuation fund, is changing its rules so that members cannot suddenly withdraw investments from their property fund in the event of a downturn. Whatever happens, we certainly need to reconsider the Australian dream of owning our own home. We could help the matter by improving our tenancy laws. FIND US ON FACEBOOK https://www.facebook.com/DailyRantAustralia/ SOURCES AustralianSuper plans for property downturn, gives itself ability to freeze funds in 'exceptional circumstances' http://www.abc.net.au/news/2018-10-10/australias-biggest-super-fund-plans-for-property-downturn/10359198 House price falls could turn out to be good, bad or downright ugly http://www.abc.net.au/news/2018-10-08/australian-housing-market-good-bad-and-ugly/10348856 Australian housing, the economic parallels with Ireland and the risk of a housing crash http://www.abc.net.au/news/2018-10-08/how-much-is-australia-in-2018-like-ireland-in-2007/10343364 Amid an epidemic of mortgage stress, a perfect financial storm is on the way, experts warn http://www.abc.net.au/news/2018-09-19/mortgage-stress-surges-as-dream-of-home-ownership-fades/10249498 Fears of housing 'fire sale' as interest-only loans roll into principal plus interest http://www.abc.net.au/news/2018-06-19/fears-as-interest-only-loans-roll-into-principal-plus-interest/9886430
Views: 4990 Daily Rant Australia
Anthony Lacavara ---  AI Learns from History
Imagine if in the early 2000's AI based computers were responsible for reviewing all mortgage applications before final approval was given. Imagine further that they were drawing on the big data repository of mortgage information for the past 30 years. It is highly likely that the real estate bust would have never occurred or that it would have been greatly mitigated. While you didn't need AI to know what was going to happen, it certainly could have shown in great detail the inevitable damage that would be inflicted upon the global financial system. And it would have given political leaders advanced warning and a real reason to start reigning it in. Perhaps in 2020 AI will avoid the next great real estate bust. But, we'll never know. This is just one example of the projects that Globalive is working on right now. Its work will be felt in medicine, media and virtually every other aspect of our world.
What Data Mining Teaches me about Teaching Statistics
This webinar discusses real-world data mining examples that illustrate and inform teaching K-12 and introductory statistics. Presented by Richard D. De Veaux, Williams College. Recorded 3-18-2009
Mozenda - Data Mining - Web Crawler - ForumExample
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: 4452 Justin McClelland
MBA 738 Data Mining for Business Intelligence | George Mason University MBA
Dr. Pallab Sanyal gives an overview MBA 738 Data Mining for Business Intelligence, an elective course in George Mason University's MBA program. George Mason MBA students have 15 credits of electives to choose courses that fit their interests and career goals. The Mason MBA currently offers the following areas of emphasis: •Accounting •Entrepreneurship •Financial Management •Information Systems Management •International Business •Leadership •Marketing •Project Management •Real Estate Learn more about areas of specialization at http://business.gmu.edu/mba-programs/curriculum/areas-emphasis/. Review all available courses and descriptions at http://business.gmu.edu/mba-programs/curriculum/courses-syllabi/.
Views: 1638 GeorgeMasonBusiness
Capture Data from Website to generate more leads - Real Estate Agent Website
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
Extraordinary Measures: The Power of GIS
Your real estate agent was right: location, location, location. In the world of Geographic Information Systems (GIS), academics and professionals design methods and applications for capturing, analyzing, and visualizing spatial (or geographic) data using a continuum spanning the use of UAVs (drones), aircraft, and/or satellites—sometimes from remote locations. Since everything has a location, anything and everything (crime, medical patients, wildlife species, etc.) can be mapped to understand new relationships, patterns, and trends to answer research questions, guide policy makers, and improve organizations’ decision-making. Partnering with discipline experts, the faculty of Claremont Graduate University’s Center for Information Systems & Technology and students and colleagues from across The Claremont Colleges collect data, produce algorithms, and design applications that can seamlessly applied in virtually every area of human endeavor, including environmental analysis, marketing, public health, survey mapping, law enforcement, and humanitarian efforts. From providing confirmation of human rights abuses in Sudan to understanding the dispersion of creosote plants in the Mojave Desert to tracking decades of reforestation at a Costa Rica natural preserve, GIS methods and applications provide academics and students, organizations, and institutions with a wealth of search as well as strategic opportunities. https://www.cgu.edu/academics/program/geographic-information-systems/ https://www.cgu.edu/school/center-for-information-systems-and-technology/ https://www.cgu.edu/ https://www.cgu.edu/news/2016/12/eyes-in-the-skies/ https://www.cgu.edu/news/2016/07/reforestation-drone-costa-rica/ Music "Silver" and "Swear" by Moby. http://mobygratis.com For more than 90 years, Claremont Graduate University has been a leader in graduate education. 40 master’s and 19 doctoral degree fields. Limited enrollment, renowned faculty, and small class sizes devoted entirely to graduate study. At CGU we put students first.
Realtor Search: Elasticsearch and Python in Practice
Aleksandar Velkoski http://www.pyvideo.org/video/3545/realtor-search-elasticsearch-and-python-practice Part of our Master Member Profile project, the REALTOR search is a Web2py-based application, leveraging Elasticsearch, that aims to provide users (staff and members) with a means to query comprehensive member profiles. With relevant data gathered and presented via an easy-to-use centralized platform, staff can leverage information to enhance services provided to members and members to enhance productivity.
Views: 4956 Next Day Video
Mozenda - Data Mining - Web Crawler  - ConsumerResearchExample
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: 1030 Justin McClelland

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