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introduction deep learning

Type:: E-books
Files:: 2
Size:: 16.3 MB
Uploaded On:: June 11, 2019, 3:44 p.m.
Added By:: bookflare
Seeders:: 3
Leechers:: 0
Info Hash:: D0A58F618CF0CD2635EA76AA6B648950E67DB5AB

This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning. The author, a longtime artificial intelligence researcher specializing in natural-language processing, covers feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and other fundamental concepts and techniques. Students and practitioners learn the basics of deep learning by working through programs in Tensorflow, an open-source machine learning framework. “I find I learn computer science material best by sitting down and writing programs,” the author writes, and the book reflects this approach

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introduction deep learning

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