Machine Learning with Neural Networks

An Introduction for Scientists and Engineers

Bernhard Mehlig

• Publisher: Cambridge University Press
• Year: 2021
• Print ISBN: 9781108494939
• eBook ISBN: 9781108849562
• Topic: Physical Sciences
• Subtopic: Mathematical & Computational Physics

This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong connections are drawn with underlying methods from statistical physics and current applications within science and engineering. Closely based around a well-established undergraduate course, this pedagogical text provides a solid understanding of the key aspects of modern machine learning with artificial neural networks, for students in physics, mathematics, and engineering. Numerous exercises expand and reinforce key concepts within the book and allow students to hone their programming skills. Frequent references to current research develop a detailed perspective on the state-of-the-art in machine learning research.

Table of contents

• Cover
• Half-title Page
• Title Page
• Copright Page
• Contents
• Acknowledgements
• 1 Introduction
• Part I Hopfield Networks
• Part II Supervised Learning
• Part III Learning without Labels
• Bibliography
• Author Index
• Subject Index