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ISBNSpecification
  SPECIFICATION
BAYESIAN METHODS FOR HACKERS (pb) 2018
Author: CAMERON DAVIDSON PILON
ISBN: 9789353063641
Year: 2018
Publisher: PEARSON EDUCATION ASIA
Category: ARTIFICIAL INTELLIGENCE
Edition: 1
Format: Paperback
Language: English
Pages: 256
 ABOUT THE TITLE
The next generation of problems will not have deterministic solutions - the solutions will be statistical that rely on mountains, or mounds, of data. Bayesian methods offer a very flexible and extendible framework to solve these types of problems. For programming students with minimal background in mathematics, this example-heavy guide emphasizes the new technologies that have allowed the inference to be abstracted from complicated underlying mathematics. Using Bayesian Methods for Hackers, students can start leveraging powerful Bayesian tools right now gradually deepening their theoretical knowledge while already achieving powerful results in areas ranging from marketing to finance.

Salient Features
- Students will masterBayesian techniques that will play an increasingly crucial role in every data scientist's toolkit
- Shows students how to solve statistically-based problems relying on mountains of data
- Teaches through realistic (non-toy) examples built with the Python PyMC library, including start-to-finish application case studies
- Gives an intuitive understanding of key concepts such as clustering, convergence, autocorrelation, and thinning.

Author: Cameron Davidson-Pilon
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 TABLE OF CONTENTS
Chapter 1: The Philosophy of Bayesian Inference
Chapter 2: A Little More on PyMC
Chapter 3: Opening the Black Box of MCMC
Chapter 4: The Greatest Theorem Never Told
Chapter 4: The Greatest Theorem Never Told
Chapter 6: Getting Our Priorities Straight
Chapter 7: Bayesian A/B Testing
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