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Date : 2015-10-12
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Bayesian Methods for Hackers Probabilistic Programming ~ Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy SciPy and Matplotlib Using this approach you can reach effective solutions in small increments without extensive mathematical intervention
Bayesian Methods for Hackers Probabilistic Programming ~ Bayesian Methods for Hackers Probabilistic Programming and Bayesian Inference Cameron DavidsonPilon New York • Boston • Indianapolis • San Francisco Toronto • Montreal • London • Munich • Paris • Madrid Capetown • Sydney • Tokyo • Singapore • Mexico City
Bayesian Methods for Hackers Probabilistic Programming ~ 1 The Philosophy of Bayesian Inference 11 Introduction You are a skilled programmer but bugs still slip into your code After a particularly difficult implementation of an algorithm you decide … Selection from Bayesian Methods for Hackers Probabilistic Programming and Bayesian Inference Book
Probabilistic Programming Bayesian Methods for Hackers ~ With collaboration from the TensorFlow Probability team at Google there is now an updated version of Bayesian Methods for Hackers that uses TensorFlow Probability TFP This is a great way to learn TFP from the basics of how to generate random variables in TFP up to full Bayesian modelling using TFP
Probabilistic Programming and Bayesian Methods for Hackers ~ If frequentist and Bayesian inference were programming functions with inputs being statistical problems then the two would be different in what they return to the user The frequentist inference function would return a number representing an estimate typically a summary statistic like the sample average etc whereas the Bayesian function would return probabilities
Bayesian Methods for Hackers Probabilistic Programming ~ Introduction to Computer Science Introduction to Computer Programming Algorithms and Data Structures Artificial Intelligence Computer Vision Machine Learning Neural Networks Game Development and Multimedia Data Communication and Networks Coding Theory Computer Security Information Security Cryptography Information Theory Computer Organization and Architecture Operating Systems Image Processing Parallel Computing Concurrent Programming Relational Database Documentoriented Database Data
An introduction to probabilistic programming now ~ Probabilistic programming for everyone Though not required for probabilistic programming the Bayesian approach offers an intuitive framework for representing beliefs and updating those beliefs based on new data Bayesian Methods for Hackers teaches these techniques in a handson way using TFP as a substrate
Bayesian Methods for Hackers Probabilistic Programming ~ Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy SciPy and Matplotlib Using this approach you can reach effective solutions in small increments without extensive mathematical intervention
CamDavidsonPilonProbabilisticProgrammingandBayesian ~ Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference yet it is hidden from readers behind chapters of slow mathematical analysis The typical text on Bayesian inference involves two to three chapters on probability theory then enters what Bayesian inference is
Bayesian inference Wikipedia ~ Bayesian inference is a method of statistical inference in which Bayes theorem is used to update the probability for a hypothesis as more evidence or information becomes available Bayesian inference is an important technique in statistics and especially in mathematical n updating is particularly important in the dynamic analysis of a sequence of data
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