Bayesian Reasoning and Machine Learning
Author: David Barber
Publisher: Cambridge University Press
ISBN: 9780521518147
Category: Computers
Page: 697
View: 549
Language: en
Pages: 697
Pages: 697
A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.
Language: en
Pages:
Pages:
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice
Language: en
Pages: 147
Pages: 147
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
Language: en
Pages: 147
Pages: 147
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
Language: en
Pages: 745
Pages: 745
This two-volume set constitutes the refereed proceedings of the workshops which complemented the 19th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in Würzburg, Germany, in September 2019. The 70 full papers and 46 short papers presented in the two-volume set were carefully reviewed
