ARTIFICIAL INTELLIGENCE MARKETING AND PREDICTING CONSUMER CHOICE


ARTIFICIAL INTELLIGENCE MARKETING AND PREDICTING CONSUMER CHOICE

Learn about the ways that artificial intelligence and machine learning methods work to enhance predictive models. Everything is explained in clear language and without recourse to equations or advanced notation. Many methods are discussed, including Bayes Nets, different ensemble methods, classification trees, and neural networks. We also review old favorites that have been greatly expanded by machine learning, such as conjoint, discrete choice modeling and MaxDiff (or maximum difference scaling). This is  a book for professionals who must apply these methods and students who want to learn about them. It Includes several downloadable market simulator programs and two bonus online chapters.


Available for purchase at Amazon.com (direct link to purchase).
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BAYES NETS - UNDERSTANDING THE BEST NEW THING

12 pages, 2013 article discusses the remarkable properties of Bayes Nets and gives examples of their use as the preeminent means of finding key drivers

 Please click here for the PDF FILE Bayes Nets Understanding the best newest thing

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BAYES NETS - UNLEASHING THEIR POWER

19 slides, an overview of this remarkable method and what it can do with examples

Please click here for the PDF FILE Bayes Nets Unleashing the power (Bayesian networks)

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PLS PATH MODELS

15 slides, explaining a regression-based method designed to predict multiple variables and group highly correlated variables so they can be analyzed, with examples

Please click here for the PDF FILE PLS path models

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