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.

Product details

• Authors: Jared M Maruskin, Jared M. Maruskin
• Publisher: Cayenne Canyon Press
• Languages: English
• Product format: Paperback / Softback
• Released: 31.01.2022
• EAN: 9781941043127
• ISBN: 978-1-941043-12-7
• No. of pages: 356
• Dimensions: 156 mm x 234 mm x 19 mm
• Weight: 541 g
• Subject: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics