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Crash Course on Naive Bayes Classification


Naive Bayes is a technique from machine learning, useful for making classifications. Naive Bayes has all sorts of applications ranging from facial recognition to weather prediction to medical diagnoses to news classifications among others. In this webinar, we provide an introduction to Naive Bayes methods through theory and coding examples. By the end of the webinar, students should acquire a strong understanding of this technique.

Kevin D. Dayaratna - Data Science
Kevin D. Dayaratna

Chief Statistician, Data Scientist, and Senior Research Fellow at The Heritage Foundation

Kevin D. Dayaratna, Ph.D. explores questions on the boundary of policy, statistics, and economics as Chief Statistician, Data Scientist, and Senior Research Fellow in The Heritage Foundation’s Center for Data Analysis (CDA). An applied statistician, he has researched and published on the use of high-powered statistical models in public policy, medical outcomes, business, economics, and professional sports among many other fields.

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