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Python Deep Learning - Third Edition

You're reading from  Python Deep Learning - Third Edition

Product type Book
Published in Nov 2023
Publisher Packt
ISBN-13 9781837638505
Pages 362 pages
Edition 3rd Edition
Languages
Concepts
Author (1):
Ivan Vasilev Ivan Vasilev
Profile icon Ivan Vasilev
Toc

Table of Contents (17) Chapters close

Preface 1. Part 1:Introduction to Neural Networks
2. Chapter 1: Machine Learning – an Introduction 3. Chapter 2: Neural Networks 4. Chapter 3: Deep Learning Fundamentals 5. Part 2: Deep Neural Networks for Computer Vision
6. Chapter 4: Computer Vision with Convolutional Networks 7. Chapter 5: Advanced Computer Vision Applications 8. Part 3: Natural Language Processing and Transformers
9. Chapter 6: Natural Language Processing and Recurrent Neural Networks 10. Chapter 7: The Attention Mechanism and Transformers 11. Chapter 8: Exploring Large Language Models in Depth 12. Chapter 9: Advanced Applications of Large Language Models 13. Part 4: Developing and Deploying Deep Neural Networks
14. Chapter 10: Machine Learning Operations (MLOps) 15. Index 16. Other Books You May Enjoy

Technical requirements

We’ll implement the example in this chapter using Python, PyTorch, and the Hugging Face Transformers library (https://github.com/huggingface/transformers). If you don’t have an environment set up with these tools, fret not—the example is available as a Jupyter notebook on Google Colab. You can find the code examples in the book’s GitHub repository: https://github.com/PacktPublishing/Python-Deep-Learning-Third-Edition/tree/main/Chapter07.

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