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Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

You're reading from  Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

Product type Book
Published in Oct 2022
Publisher Packt
ISBN-13 9781803232911
Pages 698 pages
Edition 3rd Edition
Languages
Authors (3):
Amita Kapoor Amita Kapoor
Profile icon Amita Kapoor
Antonio Gulli Antonio Gulli
Profile icon Antonio Gulli
Sujit Pal Sujit Pal
Profile icon Sujit Pal
View More author details

Table of Contents (23) Chapters

Preface 1. Neural Network Foundations with TF 2. Regression and Classification 3. Convolutional Neural Networks 4. Word Embeddings 5. Recurrent Neural Networks 6. Transformers 7. Unsupervised Learning 8. Autoencoders 9. Generative Models 10. Self-Supervised Learning 11. Reinforcement Learning 12. Probabilistic TensorFlow 13. An Introduction to AutoML 14. The Math Behind Deep Learning 15. Tensor Processing Unit 16. Other Useful Deep Learning Libraries 17. Graph Neural Networks 18. Machine Learning Best Practices 19. TensorFlow 2 Ecosystem 20. Advanced Convolutional Neural Networks 21. Other Books You May Enjoy
22. Index

Neural Network Foundations with TF

In this chapter, we learn the basics of TensorFlow, an open-source library developed by Google for machine learning and deep learning. In addition, we introduce the basics of neural networks and deep learning, two areas of machine learning that have had incredible Cambrian growth during the last few years. The idea behind this chapter is to provide all the tools needed to do basic but fully hands-on deep learning.

We will learn:

  • What TensorFlow and Keras are
  • An introduction to neural networks
  • What the perceptron and multi-layer perceptron are
  • A real example: recognizing handwritten digits

All the code files for this chapter can be found at https://packt.link/dltfchp1.

Let’s begin!

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