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Hands-On Neural Networks with TensorFlow 2.0

You're reading from  Hands-On Neural Networks with TensorFlow 2.0

Product type Book
Published in Sep 2019
Publisher Packt
ISBN-13 9781789615555
Pages 358 pages
Edition 1st Edition
Languages
Author (1):
Paolo Galeone Paolo Galeone
Profile icon Paolo Galeone

Table of Contents (15) Chapters

Preface Section 1: Neural Network Fundamentals
What is Machine Learning? Neural Networks and Deep Learning Section 2: TensorFlow Fundamentals
TensorFlow Graph Architecture TensorFlow 2.0 Architecture Efficient Data Input Pipelines and Estimator API Section 3: The Application of Neural Networks
Image Classification Using TensorFlow Hub Introduction to Object Detection Semantic Segmentation and Custom Dataset Builder Generative Adversarial Networks Bringing a Model to Production 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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