This book offers a practical, hands-on exploration of deep learning. Author François Chollet, the creator of Keras and a Google AI researcher, avoids mathematical notation, preferring instead to explain quantitative concepts via code snippets and to build practical intuition about the core ideas of machine learning and deep learning. More than 30 code examples include detailed commentary, practical recommendations, and simple high-level explanations of everything you need to know to start using deep learning to solve concrete problems.
<ASIN:1617294438>
The code examples use the Python deep-learning framework Keras, with TensorFlow as a backend engine.
Author: François Chollet Publisher: Manning Date: Nov 2017 Pages: 384 ISBN: 978-1617294433 Print: 1617294438 Kindle: free with print book Audience: AI developers Level: intermediate Category: Artificial Intelligence
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Contents include:
- The mathematical building blocks of neural networks
- Fundamentals of machine learning
- Deep learning for computer vision
- Deep learning for text and sequences
- Advanced deep learning best practices
- Generative deep learning
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T-SQL Fundamentals (Microsoft Press)
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Itzik Ben-Gan is a highly respected Microsoft Data Platform MVP, and the earlier editions of this book were already ver [ ... ]
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Functional Design (Addison-Wesley)
Author: Robert C. Martin Publisher: Addison-Wesley Date: September 2023 Pages: 384 ISBN: 978-0138176396 Print: 0138176396 Kindle: B0CGHQKGYG Audience: General Rating: 4.5 Reviewer: Kay Ewbank
This book sets out to explain the principles, patterns and practices of functional design, and why functional prog [ ... ]
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