Bayesian Programming (Chapman & Hall/CRC Machine Learning & Pattern Recognition) - Image 1

Price loading...

Chapman and Hall/CRC Bayesian Programming (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Name: Bayesian Programming (Chapman & Hall/CRC Machine Learning & Pattern Recognition)
Brand: Chapman and Hall/CRC

5 Tables, black and white; 61 Illustrati

Econometrics

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an alternative framework to deal with incomplete and uncertain data. Decision-Making Tools and Methods for Incomplete and Uncertain DataEmphasizing probability as an alternative to Boolean logic, Bayesian Programming covers new methods to build probabilistic programs for real-world applications. Written by the team who designed and implemented an efficient probabilistic inference engine to interpret Bayesian programs, the book offers many Python examples that are also available on a supplementary website together with an interpreter that allows readers to experiment with this new approach to programming. Principles and Modeling Only requiring a basic foundation in mathematics, the first two parts of the book present a new methodology for building subjective probabilistic models. The authors introduce the principles of Bayesian programming and discuss good practices for probabilistic modeling. Numerous simple examples highlight the application of Bayesian modeling in different fields. Formalism and AlgorithmsThe third part synthesizes existing work on Bayesian inference algorithms since an efficient Bayesian inference engine is needed to automate the probabilistic calculus in Bayesian programs. Many bibliographic references are included for readers who would like more details on the formalism of Bayesian programming, the main probabilistic models, general purpose algorithms for Bayesian inference, and learning problems. FAQsAlong with a glossary, the fourth part contains answers to frequently asked questions. The authors compare Bayesian programming and possibility theories, discuss the computational complexity of Bayesian inference, cover the irreducibility of incompleteness, and address the subjectivist versus objectivist epistemology of probability. The First Steps toward a Bayesian ComputerA new modeling methodology, new inference algorithms, new programming languages, and new hardware are all needed to create a complete Bayesian computing framework. Focusing on the methodology and algorithms, this book describes the first steps toward reaching that goal. It encourages readers to explore emerging areas, such as bio-inspired computing, and develop new programming languages and hardware architectures.

Product Specifications

Brand: Chapman and Hall/CRC
Model: 5 Tables, black and white; 61 Illustrati
Format: hardcover
ASIN: 1439880328
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 20 December 2013
Listed Since: 29 April 2011

Barcode

No barcode data available

Chapman and Hall/CRC Bayesian Programming (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Probability and Bayesian Modeling (Chapman & Hall/CRC Texts in Statistical Science)

Bayes Rules!: An Introduction to Applied Bayesian Modeling (Chapman & Hall/CRC Texts in Statistical Science)

Bayes Rules!: An Introduction to Applied Bayesian Modeling (Chapman & Hall/CRC Texts in Statistical Science)

Introduction to Bayesian Data Analysis for Cognitive Science (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)

Bayesian Econometric Modelling for Big Data - Chapman and Hall/CRC

CRC Press Probability and Statistical Inference Textbook

Bayesian Modeling and Computation in Python (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Networks: With Examples in R (Chapman & Hall/CRC Texts in Statistical Science)

Computational Business Analytics (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation: 32 (Chapman & Hall/CRC Biostatistics)

Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

Understanding Computational Bayesian Statistics (Wiley Series in Computational Statistics)

Introduction to Statistical Modelling and Inference

Bayesian Analysis with Python: A practical guide to probabilistic modeling

The BUGS Book: A Practical Introduction to Bayesian Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems

Understanding Advanced Statistical Methods (Chapman & Hall/CRC Texts in Statistical Science)

An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics)

Bayesian Statistical Methods (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Hierarchical Models: With Applications Using R, Second Edition

Machine Learning: A Bayesian and Optimization Perspective

Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan

Bayesian Thinking in Biostatistics (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Methods in Pharmaceutical Research (Chapman & Hall/CRC Biostatistics Series)