Fundamentals of Data Science Part II: Statistical Modeling

In Part II of this series, we cover the elements of statistical modeling, focusing on:

• validation methodology
• principles of object-oriented design
• linear and logistic regression
• generalized linear models
• causality
• time series analysis
• Bayesian statistics, including simulations in pymc3
• Modeling customer lifetime values, including a detailed study of the beta-Bernoulli/beta-binomial model, a discretized version of the classic Pareto/NBD
• an introduction to credibility theory

The theory is illustrated with simulations in Python throughout the text.

Author: Jared M. Maruskin
Publisher: Cayenne Canyon Press
Published: 01/17/2022
Pages: 356
Binding Type: Paperback
Weight: 1.10lbs
Size: 9.21h x 6.14w x 0.74d
ISBN: 9781941043127

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