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Can I read Bayesian Analysis with Python on EtoBox?
Bayesian Analysis with Python by Osvaldo Martin is a nonfiction available to read on EtoBox.
What is Bayesian Analysis with Python about?
**Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ** Key Features* A step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZ * A modern, practical and computational approach to Bayesian statistical modeling * A tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises. Book DescriptionThe 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. The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others. By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After read
Who reads Bayesian Analysis with Python?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Osvaldo Martin
- Publisher
- Packt Publishing Limited
- Published
- 2016
- Language
- EN
- ISBN
- 9781788623223
- Category
- nonfiction
- Subjects
- Computer Science, Science, Mathematics
Other editions & translations
- Building Machine Learning Systems with Python : Explore Machine Learning and Deep Learning Techniques for Building Intelligent Systems Using Scikit-learn and Te (2018)
- Hands-On Machine Learning for Algorithmic Trading : Design and Implement Investment Strategies Based on Smart Algorithms That Learn From Data Using Python (2019)
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