Overview: Predictive Analytics (PA) is an approach to analysis that has moved from being a niche approach to a mainstream approach and is often included in lists of growing technology industries. Many analysts are familiar with building basic analyses and reports in Excel, KPIs with a Business Intelligence (BI) tool, or statistical tests. PA, however, is not an approach than can be summarized by a series of rules or recipes: there is certainly science behind PA approaches, but there is also considerable "art" as well.
The "art" of PA is driven by principles derived from the science, but still allows for multiple approaches to achieve the same end. This webinar summarizes the best practices for building predictive models including both the art and the science of PA during each stage of the process, including Data Understanding, Data Preparation, Predictive Modeling and Deployment.
Why should you attend: Effective predictive modeling does not require a PhD in mathematics, statistics, or hard science fields to do well. Many effective and even famous data miners and predictive modelers have BS or BA degrees in non-technical fields. However, it does require a qualitative understanding of what algorithms do, what their limitations are, how to change their behavior, and what kind of data is necessary for building predictive models.
Areas Covered in the Session:
Who Will Benefit:
Dean Abbott is President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology. He is also Chief Scientist of SmarterRemarketer, a startup company focusing on behaviorally- and data-driven marketing attribution and web analytics. Mr. Abbott is a highly regarded and popular speaker at Predictive Analytics and Data Mining conferences, including Predictive Analytics World, Predictive Analytics Summit, the Predictive Analytics Center of Excellence, SAS Institute, DM Radio, and INFORMS.
He has served on the program committees for the KDD Industrial Track and Data Mining Case Studies workshop and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate and the UCSD Data Mining Certificate programs. Mr. Abbott has taught applied data mining and text mining courses using IBM SPSS Modeler, Statsoft Statistica, Salford Systems SPM, SAS Enterprise Miner, Tibco Spotfire Miner, IBM PredictiveInsight, Megaputer Polyanalyst, KNIME, and RapidMiner.
Live : $239.00
Corporate live : $479.00
Recorded : $289.00
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