Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems
By: Geron, Aurelien
Material type:![](/opac-tmpl/lib/famfamfam/BK.png)
Item type | Home library | Call number | Status | Notes | Date due | Barcode | Item holds |
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REGULAR | University of Wollongong in Dubai Main Collection | 006.31 GE HA (Browse shelf) | Available | Feb2020 | T0063599 |
, Shelving location: Main Collection Close shelf browser
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006.31 CH SP Spark : | 006.31 ET MA Machine learning with microsoft technologies : | 006.31 FO DA Data smart : | 006.31 GE HA Hands-on machine learning with Scikit-Learn and TensorFlow : | 006.31 GO DE Deep learning | 006.31 GR DE Deep learning neural networks : | 006.31 HA MA Machine Learning Mathematics : |
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—author Aurélien Géron 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.