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Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems / Aur�elien G�eron.

By: Material type: TextTextPublisher: India : SPD 2017Copyright date: �2017Edition: First editionDescription: xx, 545pages : illustrations ; 24 cm Carrier type:
  • volume
ISBN:
  • 9789352135219
Subject(s): Genre/Form: DDC classification:
  • 006.31  23 GEH
Summary: "Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks--Scikit-Learn and TensorFlow--author Aur�elien G�eron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started" -- Back cover.
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Item type Current library Call number Copy number Status Date due Barcode
Books Books Central Library, SUST General Stacks 006.31 GEH (Browse shelf(Opens below)) 1 Available 0074111

Includes index.

"Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks--Scikit-Learn and TensorFlow--author Aur�elien G�eron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started" -- Back cover.

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