Machine learning with neural networks : an introduction for scientists and engineers / Bernhard Mehlig, University of Gothenburg, Sweden.
By: Mehlig, Bernhard [author.].
Publisher: Cambridge, United Kingdom ; New York, NY : Cambridge University Press, ©2021Description: 249 pages cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9781108494939.Subject(s): Neural networks (Computer science) | Machine learning | SCIENCE / Physics / Mathematical & Computational | SCIENCE / Physics / Mathematical & ComputationalGenre/Form: Print books.Summary: "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"--| Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|
| On Shelf | QA76.87 .M447 2021 (Browse shelf) | Available | AU00000000019371 |
Includes bibliographical references and index.
"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"--