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02126aam a2200277 i 4500 001 439F0FF6D37711ED83DD52344BECA4DB 003 SILO 005 20230405010043 008 220531s2023 enka b 001 0 eng d 020 $a 1108835082 020 $a 9781108835084 035 $a (OCoLC)1322049214 040 $a YDX $b eng $e rda $c YDX $d UKMGB $d OCLCF $d YDX $d SILO 050 4 $a Q325.73 D76 2023 100 1 $a Drori, Iddo, $e author. 245 14 $a The science of deep learning / $c Iddo Drori. 264 1 $a Cambridge, United Kingdom ; $b Cambridge University Press, $c 2023. 300 $a xxii, 338 pages : $b illustrations (some color) ; $c 25 cm 504 $a Includes bibliographical references and index. 520 $a The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions. 650 0 $a Deep learning (Machine learning) 776 08 $i ebook version : $z 9781108891530 941 $a 1 952 $l USUX851 $d 20230907010525.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=439F0FF6D37711ED83DD52344BECA4DB 994 $a C0 $b IWAInitiate Another SILO Locator Search