Deep Learning with Python, Third Edition: Detailed Introduction

📚 Basic Information

• Book Title: Deep Learning with Python, Third Edition
• Authors: François Chollet (Creator of Keras) and Matthew Watson (Google Software Engineer)
• Publisher: Manning Publications
• Version: Third Edition (2025)
• Online Reading: https://deeplearningwithpython.io/ (Free to read)
• Language: English
• Difficulty Level: Intermediate (Requires intermediate Python skills; no prior machine learning or linear algebra knowledge needed)

🎯 Course Overview

This is an authoritative textbook on deep learning, personally authored by François Chollet, the creator of the Keras framework. The third edition is a complete rewrite of the bestselling original, incorporating the latest content such as generative AI, large language models, and diffusion models. The book is practice-oriented, building an understanding of deep learning layer by layer through code examples and projects.

🔥 Core Features of the Third Edition

New Content Coverage

• Generative AI: Includes the latest generative artificial intelligence techniques
• Transformer Architecture: Detailed introduction to attention mechanisms and Transformer models
• GPT-like Large Language Models: Teaches you how to build your own GPT-like models
• Diffusion Models: Learn about diffusion models for image generation
• Multi-framework Support: Covers Keras 3, PyTorch, JAX, and TensorFlow

Learning Approach

• Practice-first: Hands-on, code-first learning
• From Basics to Advanced: Comprehensive coverage from fundamental concepts to generative AI
• Intuitive Math Explanations: Explains mathematical concepts in an easy-to-understand way
• Project-driven: Each chapter includes practical projects and code examples

📖 Main Learning Content

Core Technology Stack

# Supported main frameworks
- Keras 3 (Primary framework)
- TensorFlow
- PyTorch
- JAX

Covered Technical Areas

1. Deep Learning Fundamentals

   • Mathematical building blocks of neural networks
   • Basic concepts of deep learning

2. Computer Vision

   • Image classification
   • Image segmentation
   • Advanced computer vision techniques

3. Natural Language Processing

   • Text classification
   • Machine translation
   • Building large language models

4. Time Series Prediction

   • Time series data processing
   • Building prediction models

5. Generative AI

   • Text generation
   • Image generation
   • Building GPT and diffusion models

6. Production Deployment

   • Model optimization and tuning
   • Real-world best practices

🎓 Target Audience

Target Readers

• Developers with intermediate Python skills
• Data scientists and machine learning enthusiasts
• Professionals looking to enter the field of deep learning
• Researchers interested in generative AI

Prerequisites

• ✅ Intermediate Python programming skills
• ❌ No machine learning experience required
• ❌ No linear algebra background required
• ❌ No prior Keras or TensorFlow experience required

💡 Learning Resources

Online Resources

• Free Online Reading: Full book content available for free on the official website
• Code Repository: Complete Jupyter notebooks provided on GitHub
• Google Colab: Code can be run directly in the browser
• Kaggle Integration: Use Kaggle datasets and model weights

Practice Environment

# Recommended runtime environment
- Google Colab (Free GPU runtime)
- Local Jupyter environment
- All code can be run on the free version of Colab

📈 Version Development History

• First Edition: Laid the foundation for deep learning with Python
• Second Edition: Added 50% new content
• Third Edition: Completely rewritten, focusing on generative AI and the latest technologies

🔧 Technical Features

Code Implementation Features

• All examples are directly runnable
• Supports multiple deep learning backends
• Provides complete project implementations
• Progressive learning path from basic to advanced

Teaching Methodology

• Combines theory with practice
• Builds understanding layer by layer
• Intuitive mathematical explanations
• Real-world application scenarios

📱 How to Get It

• Free Reading: https://deeplearningwithpython.io/
• Purchase Print Edition: Manning Publications official website
• Code Download: Free access from GitHub repository
• Run Online: Directly run all code via Google Colab

Having sold over 100,000 copies, this book is one of the most popular textbooks in the field of deep learning with Python. The release of the third edition makes it an essential resource for understanding modern deep learning and generative AI.