Learn deep learning with Keras, from setting up your environment to advanced topics like reinforcement learning and generative AI. Build, train, and optimize models for a wide range of applications.
Key Features
- Step-by-step guidance on setting up Keras and TensorFlow.
- Practical examples of deep learning concepts, including CNNs and reinforcement learning.
- Advanced techniques for building generative models, transformers, and diffusion models.
Book Description
This book provides a comprehensive guide to mastering deep learning with Keras 3, starting from the fundamentals of machine learning and neural networks to advanced techniques in reinforcement learning, transformers, and generative AI. Readers will begin with understanding the core principles of machine learning, including supervised, unsupervised, and reinforcement learning. The book explains how neural networks function and how to build them using Keras, TensorFlow, and Python. You'll dive into critical topics such as convolutional neural networks (CNNs), dropout regularization, and gradient descent optimization. As you progress, you'll learn advanced deep learning concepts like transfer learning, transformers, and the powerful Keras Functional API for building complex models. There's a focus on practical applications, such as building and evaluating deep learning models for real-world tasks, and enhancing models using GPU acceleration. You'll also explore generative models, including autoencoders and GANs, and apply them to tasks like image generation and data augmentation. By the end of the book, you'll be able to implement state-of-the-art AI models and deploy them in production environments.
What you will learn
- Install and set up Keras and TensorFlow for machine learning projects
- Understand machine learning, supervised, unsupervised, and reinforcement learning
- Implement deep learning models using Keras
- Master convolutional neural networks (CNNs)
- Build complex models with Keras Functional API
- Learn to implement and train transformers and reinforcement learning algorithms
Who this book is for
This book is ideal for data scientists, AI engineers, machine learning practitioners, and developers who want to dive into deep learning with Keras. A basic understanding of Python and machine learning concepts is helpful. It's suitable for those starting with deep learning as well as experienced developers looking to implement complex AI models.
