Bayesian Reasoning And Gaussian Processes For Machine Learning Applications

Download Bayesian Reasoning And Gaussian Processes For Machine Learning Applications full books in PDF, epub, and Kindle. Read online free Bayesian Reasoning And Gaussian Processes For Machine Learning Applications ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

Bayesian Reasoning and Gaussian Processes for Machine Learning Applications
Author :
Publisher : CRC Press
Total Pages : 147
Release :
ISBN-10 : 9781000569582
ISBN-13 : 1000569586
Rating : 4/5 (586 Downloads)

Book Synopsis Bayesian Reasoning and Gaussian Processes for Machine Learning Applications by : Hemachandran K

Download or read book Bayesian Reasoning and Gaussian Processes for Machine Learning Applications written by Hemachandran K and published by CRC Press. This book was released on 2022-04-14 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas, such as game development, decision making, and drug discovery. It is very effective for machine learning algorithms in handling missing data and extracting information from small datasets. Bayesian Reasoning and Gaussian Processes for Machine Learning Applications uses a statistical background to understand continuous distributions and how learning can be viewed from a probabilistic framework. The chapters progress into such machine learning topics as belief network and Bayesian reinforcement learning, which is followed by Gaussian process introduction, classification, regression, covariance, and performance analysis of Gaussian processes with other models. FEATURES Contains recent advancements in machine learning Highlights applications of machine learning algorithms Offers both quantitative and qualitative research Includes numerous case studies This book is aimed at graduates, researchers, and professionals in the field of data science and machine learning.


Bayesian Reasoning and Gaussian Processes for Machine Learning Applications Related Books

Bayesian Reasoning and Gaussian Processes for Machine Learning Applications
Language: en
Pages: 147
Authors: Hemachandran K
Categories: Business & Economics
Type: BOOK - Published: 2022-04-14 - Publisher: CRC Press

DOWNLOAD EBOOK

This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas, such as game deve
Bayesian Reasoning and Gaussian Processes for Machine Learning Applications
Language: en
Pages: 165
Authors: Hemachandran K
Categories: Business & Economics
Type: BOOK - Published: 2022-04-14 - Publisher: CRC Press

DOWNLOAD EBOOK

This book introduces Bayesian reasoning and Gaussian processes into machine learning applications. Bayesian methods are applied in many areas, such as game deve
Bayesian Reasoning and Machine Learning
Language: en
Pages: 739
Authors: David Barber
Categories: Computers
Type: BOOK - Published: 2012-02-02 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.
AI-Driven Intelligent Models for Business Excellence
Language: en
Pages: 293
Authors: Samala Nagaraj
Categories: Computers
Type: BOOK - Published: 2022 - Publisher: IGI Global

DOWNLOAD EBOOK

"As digital technology is taking the world in a revolutionary way and business related aspects are getting smarter this book is a potential research source on t
Efficient Reinforcement Learning Using Gaussian Processes
Language: en
Pages: 226
Authors: Marc Peter Deisenroth
Categories: Electronic computers. Computer science
Type: BOOK - Published: 2010 - Publisher: KIT Scientific Publishing

DOWNLOAD EBOOK

This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems.First, we introduce PILCO, a fu