Osvaldo Martin

Bayesian Analysis with Python - Second Edition

Introduction to statistical modeling and probabilistic programming using PyMC3 and ArviZ

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: Packt Publishing Limited
• 2 Revised edition
• Seitenzahl: 356
• Erscheinungstermin: 26. Dezember 2018
• Englisch
• Abmessung: 235mm x 191mm x 20mm
• Gewicht: 670g
• ISBN-13: 9781789341652
• ISBN-10: 1789341655
• Artikelnr.: 54936595

Autorenporträt

Osvaldo Martin is a researcher at CONICET, in Argentina. He has experience using Markov Chain Monte Carlo methods to simulate molecules and perform Bayesian inference. He loves to use Python to solve data analysis problems. He is especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling. He is an open-source developer, and he contributes to Python libraries like PyMC, ArviZ and Bambi among others. He is interested in all aspects of the Bayesian workflow, including numerical methods for inference, diagnosis of sampling, evaluation and criticism of models, comparison of models and presentation of results.