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Data Mining Map

Data mining Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.[1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for further use.[1][2][3][4] Data mining is the analysis step of the "knowledge discovery in databases" process or KDD.[5] Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.[1] Etymology[edit] In the 1960s, statisticians and economists used terms like data fishing or data dredging to refer to what they considered the bad practice of analyzing data without an a-priori hypothesis.

Difference Between Data Mining VS Predictive Analytics VS Machine Learning etc If you are a beginner in data mining and want to become at least familiar with the main concepts and terminologies, maybe the first step would be to acquire a clear bird’s eye view about the whole domain – definition, inception, classification, influences, trends – but without diving into too deep and scholastic details. And, of course, you do that by searching on Internet and skimming whatever books you have at hand. You might say that one day would be more than enough to get an overall understanding about this domain.

Scraping for Journalism: A Guide for Collecting Data Photo by Dan Nguyen/ProPublica Our Dollars for Docs news application lets readers search pharmaceutical company payments to doctors. We’ve written a series of how-to guides explaining how we collected the data. Most of the techniques are within the ability of the moderately experienced programmer. The most difficult-to-scrape site was actually a previous Adobe Flash incarnation of Eli Lilly’s disclosure site.

ONLINE OPEN-ACCESS TEXTBOOKS Search form You are here Forecasting: principles and practice Rob J Hyndman George Athana­sopou­los Statistical foundations of machine learning How to use LinkedIn for data miners If you're new here, you may want to subscribe to my RSS feed. Thanks for visiting! After the article How to use twitter for data miners, let me propose advices on using LinkedIn. First, you may already know that your LinkedIn account can be linked to display your tweets (see this link). Continue by adding the right keywords in your summary, so that other data miners can find you easily. Example of terms are data mining, predictive analytics, knowledge discovery and machine learning.

Over 100 Incredible Infographic Tools and Resources (Categorized) This post is #6 in DailyTekk’s famous Top 100 series which explores the best startups, gadgets, apps, websites and services in a given category. Total items listed: 112. Time to compile: 8+ hours. Follow @DailyTekk on Twitter to make sure you don’t miss a week! Update: Be sure to check out our latest post on infographics: Infographics Are Everywhere – Here’s How to Make Yours Go Viral. I love a good infographic!

Datamining Twitter On its own, Twitter builds an image for companies; very few are aware of this fact. When a big surprise happens, it is too late: a corporation suddenly sees a facet of its business — most often a looming or developing crisis — flare up on Twitter. As always when a corporation is involved, there is money to be made by converting the problem into an opportunity: Social network intelligence is poised to become a big business. 60+ educational resources for teaching yourself anything. From its inception, the web has always had appeal as an educational resource. Recognising the potential for remote learning, in 2002, the launch of OpenCourseWare at MIT helped propel the initiative into the spotlight, with many universities following suit and providing quality educational material available through the web. No longer is there an excuse for anyone with access to the web to say that education is outside of their reach. This collection of links and applications highlights just the tip of the iceberg of educational resources that are available on the web. If you are interested in teaching yourself a new skill or learning a new topic indepth in your spare time, hopefully some of these will be of use.