Fundamentals of Data Science Part II: Statistical Modeling
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.
Descrierea produsului
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.
Detaliile produsului
