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      Machine Learning, revised and updated edition

      1 in stock

      Firm sale: non returnable item
      SKU 9780262542524 Categories ,
      Select Guide Rating
      A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.

      Today, machine learning underlies a range of applications we use every day, from product recommendations to vo...

      £14.99

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      Description

      Product ID:9780262542524
      Product Form:Paperback / softback
      Country of Manufacture:US
      Series:The MIT Press Essential Knowledge series
      Title:Machine Learning, revised and updated edition
      Authors:Author: Ethem Alpaydin
      Page Count:280
      Subjects:Information technology: general topics, Information technology: general issues
      Description:Select Guide Rating
      A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.

      Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition--as well as some we don''t yet use everyday, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of "the new AI." This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.
       
      Alpaydin, author of a popular textbook on machine learning, explains that as "Big Data" has gotten bigger, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He describes the evolution of the field, explains important learning algorithms, and presents example applications. He discusses the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances; and reinforcement learning, when an autonomous agent learns to take actions to maximize reward. In a new chapter, he considers transparency, explainability, and fairness, and the ethical and legal implications of making decisions based on data.
      Imprint Name:MIT Press
      Publisher Name:MIT Press Ltd
      Country of Publication:GB
      Publishing Date:2021-08-17

      Additional information

      Weight254 g
      Dimensions127 × 178 × 16 mm