Hands-on machine learning with Scikit-Learn, Keras and TensorFlow : concepts, tools, and techniques to build intelligent systems / Aurélien Géron.
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TextPublisher: Beijing : O'Reilly, 2019Edition: 2nd editionDescription: xxv, 819 pages : illustrations (black and white, and colour) ; 24 cmContent type: text | still image Media type: unmediated Carrier type: volumeISBN: 9781492032649 (pbk.) :Uniform titles: Hands-on machine learning with Scikit-Learn and TensorFlow Subject(s): Machine learning | Python (Computer program language) | Computers and IT | Computers and ITDDC classification: 006.3'1 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 2 - the author 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.
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Paul Hamlyn Library | Paul Hamlyn Library | Floor 1 | 006.31 GER (Browse shelf(Opens below)) | Issued | 11/11/2024 | 06731953 | ||
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Paul Hamlyn Library | Paul Hamlyn Library | Floor 1 | 006.31 GER (Browse shelf(Opens below)) | Issued | 11/11/2024 | 06731988 | ||
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Paul Hamlyn Library | Paul Hamlyn Library | Floor 1 | 006.31 GER (Browse shelf(Opens below)) | Issued | 11/11/2024 | 06731996 |
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Previous edition: published as Hands-on machine learning with Scikit-Learn and TensorFlow. 2017.
Includes QR code.
Includes bibliographical references and 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 2 - the author 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.
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