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Through a recent series of 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 bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.
With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started.
Über die Autorin bzw. den Autor: Aurelien Geron is a Machine Learning consultant. A former Googler, he led YouTube's video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, a telecom consulting firm. Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Societe Generale), defense (Canada's DOD), and healthcare (blood transfusion). He published a few technical books (on C++, WiFi, and Internet architectures), and was a Computer Science lecturer in a French engineering school. A few fun facts: he taught his 3 children to count in binary with their fingers (up to 1023), he studied microbiology and evolutionary genetics before going into software engineering, and his parachute didn't open on the 2nd jump.
Titel: Hands-On Machine Learning with Scikit-Learn,...
Verlag: O'Reilly Media (edition 3)
Erscheinungsdatum: 2022
Einband: Paperback
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Zustand: Gut. Zustand: Gut | Seiten: 834 | Sprache: Englisch | Produktart: Bücher. Bestandsnummer des Verkäufers 38603468/3
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