Applied Deep Learning with TensorFlow 2
eBook - ePub

Applied Deep Learning with TensorFlow 2

Learn to Implement Advanced Deep Learning Techniques with Python

  1. English
  2. ePUB (mobile friendly)
  3. Only available on web
eBook - ePub

Applied Deep Learning with TensorFlow 2

Learn to Implement Advanced Deep Learning Techniques with Python

Book details
Table of contents
Citations

About This Book

Understand how neural networks work and learn how to implement them using TensorFlow 2.0 and Keras. This new edition focuses on the fundamental concepts and at the same time on practical aspects of implementing neural networks and deep learning for your research projects.

This book is designed so that you can focus on the parts you are interested in. You will explore topics as regularization, optimizers, optimization, metric analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial networks.

All the code presented in the book will be available in the form of Jupyter notebooks which would allow you to try out all examples and extend them in interesting ways. A companion online book is available with the complete code for all examples discussed in the book and additional material more related to TensorFlow and Keras. All the code will be available in Jupyter notebook format and can be openeddirectly in Google Colab (no need to install anything locally) or downloaded on your own machine and tested locally.

You will:

•Understand the fundamental concepts of how neural networks work

•Learn the fundamental ideas behind autoencoders and generative adversarial networks

•Be able to try all the examples with complete code examples that you can expand for your own projects

•Have available a complete online companion book with examples and tutorials.

This book is for:

Readers with an intermediate understanding of machine learning, linear algebra, calculus, and basic Python programming.

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Yes, you can access Applied Deep Learning with TensorFlow 2 by Umberto Michelucci in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Apress
Year
2022
ISBN
9781484280201
Edition
2
Topic
Computer Science
Subtopic
Artificial Intelligence (AI) & Semantics
Index
Computer Science

Table of contents

  1. Cover
  2. Front Matter
  3. 1. Optimization and Neural Networks
  4. 2. Hands-on with a Single Neuron
  5. 3. Feed-Forward Neural Networks
  6. 4. Regularization
  7. 5. Advanced Optimizers
  8. 6. Hyper-Parameter Tuning
  9. 7. Convolutional Neural Networks
  10. 8. A Brief Introduction to Recurrent Neural Networks
  11. 9. Autoencoders
  12. 10. Metric Analysis
  13. 11. Generative Adversarial Networks (GANs)
  14. Back Matter