Understanding Deep Learning / Simon J.D. Prince

Format:

Book

Author/Creator:

Prince, Simon J. D. (Simon Jeremy Damion), 1972- (author).

Language:

English

Subjects (All):

Deep learning (Machine learning).

Physical Description:

1 online resource : illustrations (chiefly color)

Place of Publication:

Cambridge, Massachusetts : The MIT Press, [2023]

Summary:

"An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice. Deep learning is a fast-moving field with sweeping relevance in today's increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics." -- Publisher's description.

Contents:

Introduction – Supervised learning – Shallow neural networks – Loss functions – Fitting models

Gradients and initialization – Measuring performance – Regularization – Convolutional networks – Residual networks – Transformers – Graph neural networks –Unsupervised learning – Generative adversarial networks – Normalizing flows – Variational autoencoders – Diffusion models – Reinforcement learning – Why does deep learning work?

Deep learning and ethics.

ISBN:

9780262377096

0262377098

9780262377102

0262377101