Fundamentals of Data Science Part II: Statistical ModelingIn 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