Deep learning is a subset of machine learning that has gained significant attention in recent years. It focuses on training neural networks with multiple layers to learn and make predictions from large amounts of data. Here are some of the best books on deep learning:
"Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville This book is considered the definitive work on deep learning. It covers the fundamentals of deep learning, including neural networks, optimization algorithms, and applications.
"Deep Learning with Python" by François Chollet Written by the creator of Keras, this book is a great introduction to deep learning using Python. It covers the basics of neural networks and provides practical examples using Keras.
"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron This book is a comprehensive guide to machine learning, with a focus on deep learning. It provides practical examples and exercises to help you learn and apply the concepts.
"Practical Deep Learning for Coders" by Andrew Ng This book is designed for beginners and provides a hands-on approach to learning deep learning. It covers the basics of neural networks and provides practical examples using TensorFlow.
"Deep Learning for Computer Vision with Python" by Adrian Rosebrock This book focuses on deep learning applications in computer vision. It covers topics such as image classification, object detection, and segmentation.
For more resources on deep learning, check out our Machine Learning Books.