Details zum E-Book

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.