TensorFlow 2 Pocket Primer
Seiten
2019
Mercury Learning & Information (Verlag)
978-1-68392-460-9 (ISBN)
Mercury Learning & Information (Verlag)
978-1-68392-460-9 (ISBN)
Introduces beginners to basic machine learning algorithms using TensorFlow 2. The book is intended to be a fast-paced introduction to various ""core"" features of TensorFlow, with code samples that cover machine learning and TensorFlow basics.
As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to info@merclearning.com.
Features:
Uses Python for code samples
Covers TensorFlow 2 APIs and Datasets
Includes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMs
Features the companion files with all of the source code examples and figures (download from the publisher)
As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to info@merclearning.com.
Features:
Uses Python for code samples
Covers TensorFlow 2 APIs and Datasets
Includes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMs
Features the companion files with all of the source code examples and figures (download from the publisher)
Campesato Oswald : Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).
1: Introduction to TensorFlow 2
2: Useful TensorFlow 2 APIs
3: TensorFlow 2 Datasets
4: Linear Regression
5: Working with Classifiers
Appendix: TF2, Keras, and Advanced Topics
Index
On the Companion Files:
(available from the publisher for downloading)
Source code samples from the text
Figures
| Erscheinungsdatum | 19.07.2019 |
|---|---|
| Reihe/Serie | Pocket Primer |
| Sprache | englisch |
| Gewicht | 336 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Informatik ► Web / Internet | |
| ISBN-10 | 1-68392-460-6 / 1683924606 |
| ISBN-13 | 978-1-68392-460-9 / 9781683924609 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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