ler totalmente Linear Algebra and Learning from Data

Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation. _x0007_ Thefirst textbook designed to teach linear algebra as a tool for deep learning _x0007_ From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra _x0007_ Includes the necessary background from statistics and optimization _x0007_ Explains stochasticgradient descent, the key algorithim of deep learning, in detail

Procurando Linear Algebra and Learning from Data? Aqui você encontra tudo sobre este livro de Gilbert (Massachusetts Institute of Technology) Strang, publicado por Wellesley-Cambridge Press,U.S. em 31 de janeiro de 2019. Nesta página estão a descrição da obra, os detalhes da edição (446 páginas) e os formatos disponíveis para baixar: pdf, epub, txt, djvu. Se você gosta de Livros Internacionais, Ciências Tecnológicas, Matemática, Matemática Pura, Matemática Discreta, explore também outros títulos da mesma categoria no Encontrando os melhores livros. Veja ainda as outras obras de Gilbert (Massachusetts Institute of Technology) Strang em nosso catálogo.