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Python Deep Learning

You're reading from Python Deep Learning Understand how deep neural networks work and apply them to real-world tasks

Product type Paperback

Published in Nov 2023

Publisher Packt

ISBN-13 9781837638505

Length 362 pages

Edition 3rd Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Author (1):

Ivan Vasilev

View More author details

Table of Contents (17) Chapters

Preface

1. Part 1:Introduction to Neural Networks

2. Chapter 1: Machine Learning – an Introduction FREE CHAPTER

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

Why subscribe?

16. Other Books You May Enjoy

Technical requirements

We’ll implement the examples in this chapter using Python, PyTorch, TensorFlow (TF), and Hugging Face (HF) Transformers, among others. If you don’t have an environment set up with these tools, fret not – the examples are available as Jupyter Notebooks on Google Colab. You can find the code examples in this book’s GitHub repository: https://github.com/PacktPublishing/Python-Deep-Learning-Third-Edition/tree/main/Chapter10.

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Authors (1)

Ivan Vasilev

Ivan Vasilev

Ivan Vasilev started working on the first open source Java deep learning library with GPU support in 2013. The library was acquired by a German company, with whom he continued its development. He has also worked as a machine learning engineer and researcher in medical image classification and segmentation with deep neural networks. Since 2017, he has focused on financial machine learning. He co-founded an algorithmic trading company, where he's the lead engineer. He holds an MSc in artificial intelligence from Sofia University St. Kliment Ohridski and has written two previous books on the same topic.

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