Publisher's Synopsis
In a world driven by artificial intelligence, neural networks and deep learning are transforming entire sectors, from healthcare and industry to automation and content creation. Neural Networks with TensorFlow: From Fundamentals to Practical Applications is an essential guide for those who want to understand and effectively apply these technologies in a professional way.
In this book, you will be guided from the fundamentals of neural networks to building advanced models using TensorFlow, one of the most powerful frameworks on the market. The book covers essential concepts such as activation functions, backpropagation, hyperparameter optimization, and regularization, as well as exploring modern architectures like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs).
With both theoretical and practical approaches, this book presents fundamental techniques for training, tuning, and scaling deep learning models. You will learn how to efficiently prepare data, implement transferable learning, optimize neural networks for mobile device execution with TensorFlow Lite, and deploy models with TensorFlow Serving. Furthermore, ethical challenges and best practices in the development of responsible artificial intelligence will be explored.
Whether you're a student, a technology professional, or an AI enthusiast, this book will provide the tools and knowledge needed to turn theory into innovative solutions. By the end of the reading, you will have a solid foundation to create, train, and implement neural networks that make a difference in the real world.
