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Hands-On Neural Networks with TensorFlow 2.0

You're reading from   Hands-On Neural Networks with TensorFlow 2.0 Understand TensorFlow, from static graph to eager execution, and design neural networks

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Product type Paperback
Published in Sep 2019
Publisher Packt
ISBN-13 9781789615555
Length 358 pages
Edition 1st Edition
Languages
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Author (1):
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Paolo Galeone Paolo Galeone
Author Profile Icon Paolo Galeone
Paolo Galeone
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Neural Network Fundamentals
2. What is Machine Learning? FREE CHAPTER 3. Neural Networks and Deep Learning 4. Section 2: TensorFlow Fundamentals
5. TensorFlow Graph Architecture 6. TensorFlow 2.0 Architecture 7. Efficient Data Input Pipelines and Estimator API 8. Section 3: The Application of Neural Networks
9. Image Classification Using TensorFlow Hub 10. Introduction to Object Detection 11. Semantic Segmentation and Custom Dataset Builder 12. Generative Adversarial Networks 13. Bringing a Model to Production 14. Other Books You May Enjoy

Summary

In this chapter, we went through the ML algorithm families from a general and theoretical point of view. It is essential to have good knowledge of what machine learning is, how algorithms are categorized, what kind of algorithms are used given a certain task, and how to become familiar with all the concepts and the terminology that's used among machine learning practitioners.

In the next chapter, Chapter 2, Neural Networks and Deep Learning, we will focus on neural networks. We will understand the strengths of machine learning models, how is it possible to make a network learn, and how, in practice, a model parameter update is performed.

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Hands-On Neural Networks with TensorFlow 2.0
Published in: Sep 2019
Publisher: Packt
ISBN-13: 9781789615555
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