menu
{ "item_title" : "Fundamentals of Machine Learning for Predictive Data Analytics, second edition", "item_author" : [" "], "item_description" : "The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.", "item_img_path" : "https://covers2.booksamillion.com/covers2/ebook/01/11/9780262361101_b.jpg", "price_data" : { "retail_price" : "49.99", "our_price" : "49.99", "club_price" : "49.99", "savings_pct" : "0", "savings_amt" : "0.00", "discount_pct" : "10", "club_savings_amt" : "0", "club_savings_pct" : "0" } }
Fundamentals of Machine Learning for Predictive Data Analytics, second edition|John D. Kelleher
Fundamentals of Machine Learning for Predictive Data Analytics, second edition : Algorithms, Worked Examples, and Case Studies
Download
Format: EPUB What's this?
Language: eng

This item is only available to U.S. billing addresses.

Other Available Formats

EPUB
49.99
Hardcover
$80.00

show all formats

Overview

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

This item is Non-Returnable

Details

  • ISBN: 9780262361101
  • Publisher: MIT Press
  • Imprint: The MIT Press
  • Date: Oct 2020
  • Seller Statement: Sold by Random House WHS

BAM Customer Reviews