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Bayesian analysis with Python introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ

The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models...

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Bibliographic Details
Main Author: Martin, Osvaldo
Format: eBook
Language:English
Published: Birmingham, UK Packt Publishing 2018
Edition:Second edition
Subjects:
Bayesian Statistical Decision Theory / Http://id.loc.gov/authorities/subjects/sh85012506
Python (computer Program Language) / Fast
Natural Language Processing
Python (computer Program Language) / Http://id.loc.gov/authorities/subjects/sh96008834
Théorie De La Décision Bayésienne
Bayesian Statistical Decision Theory / Fast
Traitement Automatique Des Langues Naturelles
Natural Language Processing (computer Science) / Fast
Python (langage De Programmation)
Natural Language Processing (computer Science) / Http://id.loc.gov/authorities/subjects/sh88002425
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • Bayesian analysis with Python : introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ
  • Dedication
  • Foreword
  • Contributors
  • Table of Contents
  • Foreword
  • Chapter 1: Thinking Probabilistically
  • Chapter 2: Programming Probabilistically
  • Chapter 3: Modeling with Linear Regression
  • Chapter 4: Generalizing Linear Models
  • Chapter 5: Model Comparison
  • Chapter 6: Mixture Models
  • Chapter 7: Gaussian Processes
  • Chapter 8: Inference Engines
  • Chapter 9: Where To Go Next?
  • Other Books You May Enjoy
  • Index

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