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.
PRP: 330.25 Lei
Acesta este Prețul Recomandat de Producător. Prețul de vânzare al produsului este afișat mai jos.
297.23Lei
297.23Lei
330.25 LeiPrimești 297 puncte
Livrare in 2-4 saptamani
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
