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Attributes of Bayesian Modeling and Computation in Python PDF
Bayesian Modeling and Computation in Python PDF aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory.
The book starts with a refresher of the Bayesian Inference concepts. The second chapter introduces modern methods for Exploratory Analysis of Bayesian Models. With an understanding of these two fundamentals the subsequent chapters talk through various models including linear regressions, splines, time series, Bayesian additive regression trees. The final chapters include Approximate Bayesian Computation, end to end case studies showing how to apply Bayesian modelling in different settings, and a chapter about the internals of probabilistic programming languages. Finally the last chapter serves as a reference for the rest of the book by getting closer into mathematical aspects or by extending the discussion of certain topics.
This book is written by contributors of PyMC3, ArviZ, Bambi, and Tensorflow Probability among other libraries.
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This book is one of the best-selling books for the subject of science and math for all students and professionals around the world who aspire to achieve excellency in their courses and field for better understanding and teaching their pupils and themselves. It is a must read at-least once a lifetime, whether or not you find yourself related to the subject or not. So download book Bayesian Modeling and Computation in Python PDF
The Writers
Osvaldo A. Martin is a Researcher at IMASL-CONICET in Argentina and the Department of Computer Science from Aalto University in Finland. He has a PhD in biophysics and structural bioinformatics. Over the years he has become increasingly interested in data analysis problems with a Bayesian flavor. He is especially motivated by the development and implementation of software tools for Bayesian statistics and probabilistic modeling.
Ravin Kumar is a Data Scientist at Google and previously worked at SpaceX and sweetgreen among other companies. He has an M.S in Manufacturing Engineering and a B.S in Mechanical Engineering. He found Bayesian statistics to be an excellent tool for modeling organizations and informing strategy. This interest in flexible statistical modeling led to a warm welcoming open source community which he is honored to be a member of now.
Junpeng Lao is a Data Scientist at Google. Prior to that he did his PhD and subsequently worked as a postdoc in Cognitive Neuroscience. He developed a fondness for Bayesian Statistics and generative modeling after working primarily with Bootstrapping and Permutation during his academic life.
Proportions of Bayesian Modeling and Computation in Python PDF
- Publisher : Chapman and Hall/CRC; 1st edition (December 29, 2021)
- Language : English
- Hardcover : 398 pages
- International Standard Book Number-10 : 036789436X
- International Standard Book Number-13 : 978-0367894368
- Item Weight : 2.27 pounds
- Dimensions : 7 x 1 x 10 inches
Reviews From Customers
Lisa
Simply perfect
July 24, 2020
I love the simplicity and details of this book! Love the color categories too. As a novice bird watcher in the pandemic world I quickly was obsessed with all the birds I could attract by reading through what they liked. Loved being able to learn about how to identify them. I’ve identified over 25 different birds in my own back yard.
Gloria Malone
Great pictures and information
December 27, 2020
I bought this for my mom for Christmas. She has a number of bird feeders outside her front window and my parents argue over what types of birds were visiting. (they don’t own smartphones or use computers very much) The book is on the smaller size but the main picture of the bird is in full color and takes up a whole page. Information is on the accompanying page and it is just what the casual birdwatcher needs. She’s only had it for a couple of days but has already read most of it and has been able to identify a few of the birds they were unsure about. She has commented multiple times already how much she enjoys it.
johnc
Fun referral while watching the birds.
June 7, 2022
I have enjoyed this so much I ordered one for family in IL and friends in KY. Both have said how much
they too have enjoyed their books.
RF
TOP 1000 REVIEWER
Great Book
December 28, 2021
I bought this for my son for Christmas. He is already using it. Beautiful images and information.
Jill Deubner
Great find.
September 27, 2020
Spouse loved it! You can find a bird by color which is super helpful.
CACA
Ohio Birds
June 11, 2020
This is a nice, comprehensive paperback book with good photos of birds. I recommend this. Bird description, information and photo are on one page. Priced right for all the good information.
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