Fundamentals of Deep Learning

This book provides a detailed exploration of deep learning concepts, including neural networks, autoencoders, sequence analysis, and reinforcement learning.

It is designed for Python-proficient programmers and computer science majors to grasp the intuition behind deep learning innovations without jargon.

The book covers topics such as building complex image analysis networks, effective dimensionality reduction, and interpreting complex machine learning models.