Bayesian Analysis with Python
Bayesian inference uses probability distributions and Bayes' theorem to build flexible models. The book uses PyMC3 to abstract all the mathematical and computational details from this process allowing readers to solve a wide range of problems in data science.
Offered by
Difficulty Level
Intermediate
Completion Time
11h52m
Language
English
About Book
Who Is This Book For?
If you are a student, data scientist, researcher, or a developer looking to get started with Bayesian data analysis and probabilistic programming, this book is for you. The book is introductory so no previous statistical knowledge is required, although some experience in using Python and NumPy is expected.
Bayesian Analysis with Python
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 11h52m total length
Thinking probabilistically
Programming probabilistically
Modeling with Linear Regression
Generalizing Linear Models
Model Comparison
Mixture Models
Gaussian Processes
Inference Engines
Where To Go Next?
Related Resources
Access Ready-to-Use Books for Free!
Get instant access to a library of pre-built books—free trial, no credit card required. Start training your team in minutes!