Keras 3
The Comprehensive Guide to Deep Learning with the Keras API and Python
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
Harness the power of AI with this guide to using Keras! Start by reviewing the fundamentals of deep learning and installing the Keras API. Next, follow Python code examples to build your own models, and then train them using classification, gradient descent, and regularization. Design large-scale, multilayer models and improve their decision making with reinforcement learning. With tips for creating generative AI models, this is your cutting-edge resource for working with deep learning!
Highlights include:
1) Neural networks
2) Gradient descent
3) Classification
4) Regularization
5) Convolutional neural networks (CNNs)
6) Functional API
7) Transformer architecture
8) Reinforcement learning
9) Autoencoders
10) Stable Diffusion
Tools to learn more effectively
Saving Books
Keyword Search
Annotating Text
Listen to it instead
Information
Table of contents
- Notes on Usage
- 1 Introduction
- 2 Introduction to the Core of Machine Learning
- 3 Fundamentals of Gradient Descent
- 4 Classification Through Gradient Descent
- 5 Deep Dive into Keras
- 6 Regularization Techniques
- 7 Convolutional Neural Networks
- 8 Exploring the Keras Functional API
- 9 Understanding Transformers
- 10 Reinforcement Learning: The Secret Sauce
- 11 Autoencoders and Generative AI
- 12 Advanced Generative AI: Stable Diffusion
- 13 Recap of Key Concepts
- The Author
- Index
- Service Pages
- Legal Notes