The Little Book of Deep Learning

A concise and informative guide covering key topics in deep learning, machine learning, and neural networks. Explore foundations, model architectures, and practical applications.

Introduction

The Little Book of Deep Learning by François Fleuret is a concise and informative guide that covers key topics in deep learning, machine learning, and neural networks.

Highlights

• Covers foundations of machine learning, efficient computation, and training techniques
• Explores model components and architectures including MLPs, CNNs, and Transformers
• Discusses applications of deep learning for prediction, synthesis, and the compute schism

Recommendation

This book is recommended for anyone interested in gaining a solid understanding of the core concepts and practical applications of deep learning. It provides a comprehensive yet accessible overview of the field, making it a valuable resource for both beginners and experienced practitioners.