Statistical mechanics of learning / A. Engel, C. van den Broeck.
Engel, A. (Andreas), 1957-Call Number | 006.3 |
Author | Engel, A. 1957- author. |
Title | Statistical mechanics of learning / A. Engel, C. van den Broeck. |
Physical Description | 1 online resource (xi, 329 pages) : digital, PDF file(s). |
Notes | Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
Summary | Learning is one of the things that humans do naturally, and it has always been a challenge for us to understand the process. Nowadays this challenge has another dimension as we try to build machines that are able to learn and to undertake tasks such as datamining, image processing and pattern recognition. We can formulate a simple framework, artificial neural networks, in which learning from examples may be described and understood. The contribution to this subject made over the last decade by researchers applying the techniques of statistical mechanics is the subject of this book. The authors provide a coherent account of various important concepts and techniques that are currently only found scattered in papers, supplement this with background material in mathematics and physics and include many examples and exercises to make a book that can be used with courses, or for self-teaching, or as a handy reference. |
Added Author | Broeck, C. van den 1954- author. |
Subject | NEURAL NETWORKS (COMPUTER SCIENCE) LEARNING. ARTIFICIAL INTELLIGENCE. |
Multimedia |
Total Ratings:
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Summary | Learning is one of the things that humans do naturally, and it has always been a challenge for us to understand the process. Nowadays this challenge has another dimension as we try to build machines that are able to learn and to undertake tasks such as datamining, image processing and pattern recognition. We can formulate a simple framework, artificial neural networks, in which learning from examples may be described and understood. The contribution to this subject made over the last decade by researchers applying the techniques of statistical mechanics is the subject of this book. The authors provide a coherent account of various important concepts and techniques that are currently only found scattered in papers, supplement this with background material in mathematics and physics and include many examples and exercises to make a book that can be used with courses, or for self-teaching, or as a handy reference. |
Notes | Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
Subject | NEURAL NETWORKS (COMPUTER SCIENCE) LEARNING. ARTIFICIAL INTELLIGENCE. |
Multimedia |