Bayesian Analysis with Python (3rd Edition)
Bayesian Analysis with Python: A practical guide to probabilistic modeling
English | 2024 | ISBN: 1805127160 | 503 Pages | EPUB (True) | 44 MB
English | 2024 | ISBN: 1805127160 | 503 Pages | EPUB (True) | 44 MB
The third edition of Bayesian Analysis with Python serves as an introduction to the main concepts of applied Bayesian modeling using PyMC, a state-of-the-art probabilistic programming library, and other libraries that support and facilitate modeling like ArviZ, for exploratory analysis of Bayesian models; Bambi, for flexible and easy hierarchical linear modeling; PreliZ, for prior elicitation; PyMC-BART, for flexible non-parametric regression; and Kulprit, for variable selection.