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{ "item_title" : "Bayesian Reasoning and Gaussian Processes for Machine Learning Applications", "item_author" : [" Hemachandran K", "Shubham Tayal", "Preetha Mary George "], "item_description" : "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.FEATURESContains recent advancements in machine learningHighlights applications of machine learning algorithmsOffers both quantitative and qualitative researchIncludes numerous case studiesThis book is aimed at graduates, researchers, and professionals in the field of data science and machine learning.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/0/36/775/847/0367758474_b.jpg", "price_data" : { "retail_price" : "150.00", "online_price" : "150.00", "our_price" : "150.00", "club_price" : "150.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Bayesian Reasoning and Gaussian Processes for Machine Learning Applications|Hemachandran K

Bayesian Reasoning and Gaussian Processes for Machine Learning Applications

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Overview

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.

This item is Non-Returnable

Details

  • ISBN-13: 9780367758479
  • ISBN-10: 0367758474
  • Publisher: CRC Press
  • Publish Date: April 2022
  • Dimensions: 10 x 7 x 0.38 inches
  • Shipping Weight: 1.06 pounds
  • Page Count: 133

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