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Machine learning with python : principles and practical techniques

By: Material type: TextTextPublication details: New York : Cambridge University Press, ©2024Description: xi, 1096 p. : ill. ; 25 cmISBN:
  • 9781009170246
Subject(s): DDC classification:
  • 006.31 BHA-M
Summary: "Machine learning (ML) has become a dominant problem-solving technique in the modern world, with applications ranging from search engines and social media to self-driving cars and artificial intelligence (AI). This lucid textbook presents the theoretical foundations of ML algorithms, and then illustrates each concept with its detailed implementation in Python to allow beginners to effectively implement the principles in real-world applications. All major techniques, such as regression, classification, clustering, deep learning, and association mining, have been illustrated using step-by-step coding instructions to help inculcate a "learning by doing" approach. The book has no prerequisites, and covers the subject from the ground up, including a detailed introductory chapter on the Python language. As such, it is going to be a valuable resource not only for students of computer science, but also for anyone looking for a foundation in the subject, as well as professionals looking for a ready reckoner"--
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Books Books IIITD General Stacks Computer Science and Engineering 006.31 BHA-M (Browse shelf(Opens below)) Checked out 30/12/2024 013132
Total holds: 0

Includes bibliographical references and index

"Machine learning (ML) has become a dominant problem-solving technique in the modern world, with applications ranging from search engines and social media to self-driving cars and artificial intelligence (AI). This lucid textbook presents the theoretical foundations of ML algorithms, and then illustrates each concept with its detailed implementation in Python to allow beginners to effectively implement the principles in real-world applications. All major techniques, such as regression, classification, clustering, deep learning, and association mining, have been illustrated using step-by-step coding instructions to help inculcate a "learning by doing" approach. The book has no prerequisites, and covers the subject from the ground up, including a detailed introductory chapter on the Python language. As such, it is going to be a valuable resource not only for students of computer science, but also for anyone looking for a foundation in the subject, as well as professionals looking for a ready reckoner"--

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