UID:
almahu_9949065262402882
Format:
1 online resource (xiv, 371 pages) :
,
digital, PDF file(s).
ISBN:
9781108955652 (ebook)
Content:
This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking.
Note:
Title from publisher's bibliographic system (viewed on 22 Feb 2021).
Additional Edition:
Print version: ISBN 9781108845359
Language:
English
Subjects:
Computer Science
,
Education
,
Biology
URL:
https://doi.org/10.1017/9781108955652
URL:
Volltext
(URL des Erstveröffentlichers)
Bookmarklink
