01462nam a22002417a 450000500170000000800410001702000180005804000130007608200180008924501120010726000500021930000170026950000180028652007590030454600080106365000210107165000160109270000260110870000210113470000220115570000230117770000200120020260713172925.0260713s2024    |||||||| |||| 00| 0 eng d  a9781617296482  cPK-LaUMT  a006.315bMAT-10aMath and architectures of deep learning /cKrishnendu Chaudhury . . . [et al.] ; foreword by Prith Banerjee  aShelter Island :bManning Publications,c2024  axxvi, 523 p.  aIndex present  aDiscover what's going on inside the black box! To work with deep learning you'll have to choose the right model, train it, preprocess your data, evaluate performance and accuracy, and deal with uncertainty and variability in the outputs of a deployed solution. This book takes you systematically through the core mathematical concepts, linear algebra, and Bayesian inference, all from a deep learning perspective. Math and archtectures of deep learning teaches the math, theory, and programming principles of deep learning models laid out side by side, and then puts them into practice with well-annotated Python code. You'll progrress from algebra, calculus, and statistics all the way to state-of-the-art DL architectures taken from the latest research  aEng  aMachine learning  aMathematics1 aChaudhury, Krishnendu1 aAshok, Ananya H.1 aNarumanchi, Sujay1 aShankar, Devashish1 aBanerjee, Prith