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Channel: Data Mining & Predictive Analytics - Eric King RSS Feed for Data Mining & Predictive Analytics - Eric King

 

Displaying 1–15 (of 19)

Title
Eric King Talks with SearchBusinessAnalytics about How to Develop a Predictive Analytics Strategy

 Summary
 In this interview, Eric King explains the importance of having a strategy before diving into predictive analytics.
How to Mine Scientific Business Intelligence in the Cloud
Data Mining: Failure to Launch: How to Get Predictive Modeling Off the Ground and into Orbit

 Summary
 Attend this live webinar to learn how to get started with data mining and overcome limitations that cause data mining projects to fall short of their potential.  This webinar is intended for stakeholders, functional managers and business practitioners in business, industry, government and academia, who have made substantial investments in data collection, storage, retrieval, visualization and basic analysis but may not have the technical or strategic experience necessary to chart an effective road map to uncover the valuable predictive insights hidden within their existing data. No prior knowledge is required. 

Check the webinar page for the next scheduled presentation.

Data Mining Group

 Summary
 The Data Mining Group (DMG) is an independent, vendor-led group that develops data mining standards, such as the Predictive Model Markup Language (PMML).
Data Mining Job Board: KDnuggets Jobs

 Summary
 Jobs in data mining, knowledge discovery, analytics, bioinformatics and statistics
KDD Cup 2007

 Summary
 Details about the 2007 KDD Cup, including winners.
PAKDD 2007 Data Mining Competition

 Summary
 The 11th Pacific-Asia Knowledge Discovery and Data Mining Conference (PAKDD 2007) hosted the 2007 data mining competition, co-organized by the Singapore Institute of Statistics. Competition details and information about the winners.
TDWI Report - Predictive Analytics: Extending the Value of your Data Warehousing Investment

 Summary
 This report is designed for the business or technical manager who oversees a business intelligence (BI) environment and wishes to learn the best practices and pitfalls of implementing a predictive analytics capability. The report defines predictive analytics as a form of BI that uncovers relationships and patterns, within large volumes of data, that can be used to predict future behavior and events. Unlike other BI technologies, predictive analytics is forward-looking, using past events to anticipate the future.

 

13th International Conference on Knowledge Discovery and Data Mining

 Summary
 The thirteenth ACM SIGKDD conference, held in August of 2007, provided a forum for researchers from academia, industry, and government, developers, practitioners, and the data mining user community to share their research and experience. View presentations from this conference online.
ACM SIG on Knowledge Discovery and Data Mining

 Summary
 The primary focus of the SIGKDD is to provide the premier forum for advancement and adoption of the "science" of knowledge discovery and data mining.
ACM SIG-KDD Explorations Newsletter

 Summary
 Explorations is published twice yearly, in June/July and in December/January. The newsletter is distributed in hardcopy form to all members of the ACM SIGKDD. It is also sent to ACM's network of libraries. Online versions are available on the web free to the general public. The newsletter's goal is to make the SIGKDD Newsletter an informative, rapid means of publication and dynamic forum for communication with the Knowledge discovery and data mining community.
Data Mining Application Workshop

 Summary
 Throughout the workshop, the CRISP-DM model will be used to guide participants through the steps of the data mining process, and the attendees themselves will complete the entire data mining process during the workshop by solving simple data mining problems through a staged progression.
Data Mining Job Board: Data Shaping

 Summary
 DataShaping.com is an analytic job board. Specializing in business intelligence, statistics, analytics, data management, data mining, data analysis, SAS Programming, CRM, artificial intelligence, web mining, Six Sigma, operations research, risk management, database marketing and quant.
Data Mining Techniques, Tools and Tactics

 Summary
 This two-day course presents an in-depth examination of the data mining process at a functional level. Attendees will observe and participate in demonstrations of computer-guided analytical techniques for extracting and interpreting complex business rules from data. If you desire a rapid and substantial boost in your understanding of data mining concepts, tools, techniques and supporting methods, then this course is designed for you.
Data Mining: Levels I, II and III

 Summary

DATA MINING: LEVEL I An Intensive Overview of Strategy, Best Practices and Case Studies for Predictive Analytics

DATA MINING: LEVEL II A Tactical Drill-Down of the Data Mining Process, Methods, Tools and Techniques

DATA MINING: LEVEL III A Hands-On Application Workshop for Data Mining Practitioners

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