Python machine learning: machine learning and deep learning with Python, scikit-learn, and TensorFlow 2
Third edition. - Birmingham ; Mumbai: Packt, December 2019
Online
Monographie, Elektronische Ressource
- 1 Online-Ressource (xxi, 741 Seiten)
Ermittle Ausleihstatus...
Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning. Key Features Third edition of the bestselling, widely acclaimed Python machine learning book Clear and intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practices Book Description Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.
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Python machine learning: machine learning and deep learning with Python, scikit-learn, and TensorFlow 2
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Verantwortlichkeitsangabe: | Sebastian Raschka, Vahid Mirjalili |
Autor/in / Beteiligte Person: | Raschka, Sebastian ; Mirjalili, Vahid |
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Ausgabe: | Third edition |
Veröffentlichung: | Birmingham ; Mumbai: Packt, December 2019 |
Medientyp: | Monographie |
Datenträgertyp: | Elektronische Ressource |
Umfang: | 1 Online-Ressource (xxi, 741 Seiten) |
ISBN: | 9781789958294 ebook |
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