Welcome to the resources page for the Deep Learning course, specifically for course number 307. Here, you will find a curated list of books that are highly recommended for further reading and study in the field of deep learning.
Recommended Books
Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
- This comprehensive book is considered the圣经 of deep learning, providing a deep dive into the theory and algorithms behind deep neural networks.
Neural Networks and Deep Learning by Michael A. Nielsen
- A free book that introduces the basic concepts of neural networks and deep learning. It's a great starting point for beginners.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron
- This book is a hands-on introduction to machine learning with a focus on deep learning. It's suitable for readers with basic programming knowledge.
Further Reading
- Check out our Deep Learning Tutorial for step-by-step guides and practical exercises.
Deep Learning Book
- Learn about the latest trends in deep learning by exploring our Deep Learning Research Papers.
Deep Learning Research Papers
- For those interested in the history and evolution of deep learning, read our Deep Learning History article.
Deep Learning History
By exploring these resources, you'll gain a deeper understanding of deep learning and be well-equipped to tackle advanced topics in the field.