TensorFlow 2 Pocket Primer / / Oswald Campesato.
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 TensorFlo...
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Place / Publishing House: | Dulles, VA : : Mercury Learning and Information, , [2019] ©2019 |
Year of Publication: | 2019 |
Language: | English |
Series: | Pocket Primer
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Online Access: | |
Physical Description: | 1 online resource (252 p.) |
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Other title: | Frontmatter -- Contents -- Preface -- Chapter 1. Introduction to TensorFlow 2 -- Chapter 2. Useful TF 2 APIs -- Chapter 3. TF 2 Datasets -- Chapter 4. Linear Regression -- Chapter 5. Working with Classifiers -- Appendix: TF 2, Keras, and Advanced Topics -- Index |
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Summary: | 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 samplesCovers TensorFlow 2 APIs and DatasetsIncludes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMsFeatures the companion files with all of the source code examples and figures (download from the publisher) |
Format: | Mode of access: Internet via World Wide Web. |
ISBN: | 9781683924616 |
Access: | restricted access |
Hierarchical level: | Monograph |
Statement of Responsibility: | Oswald Campesato. |