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- Author: Oswald Campesato
- Publisher: Mercury Learning and Information
- ISBN-10: 1683923642
- ISBN-13: 9781683923640
- Format: 15.2 x 22.9 x 0.9 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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Description
As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to TensorFlow 1.x fundamentals for basic machine learning algorithms in TensorFlow. It is intended to be a fast-paced introduction to various "core" features of TensorFlow, with code samples that cover deep learning and TensorFlow basics. 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 writing to [email protected].
Features:
- Uses Python for code samples
- Covers TensorFlow APIs and Datasets
- Assumes the reader has very limited experience
- Companion files with all of the source code examples (download from the publisher)
EXTRA 10 % discount with code: EXTRA
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The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Oswald Campesato
- Publisher: Mercury Learning and Information
- ISBN-10: 1683923642
- ISBN-13: 9781683923640
- Format: 15.2 x 22.9 x 0.9 cm, minkšti viršeliai
- Language: English English
As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to TensorFlow 1.x fundamentals for basic machine learning algorithms in TensorFlow. It is intended to be a fast-paced introduction to various "core" features of TensorFlow, with code samples that cover deep learning and TensorFlow basics. 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 writing to [email protected].
Features:
- Uses Python for code samples
- Covers TensorFlow APIs and Datasets
- Assumes the reader has very limited experience
- Companion files with all of the source code examples (download from the publisher)
Reviews