000			01138nam a2200181 4500
005			20250710115325.0
008			250710b |||||||| |||| 00| 0 eng d
020			_a9780262039512
082			_a 006.31 CHA
100			_aCharniak, Eugene
245			_a Introduction to deep learning
260			_aMassachusetts: _bThe MIT Press; _cc2018.
300			_axii, 174p.
500			_aIncludes index.
520			_aA project-based guide to the basics of deep learning. 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.
650			_aComputational learning theory
942			_2ddc _n0 _cC
999			_c30514 _d30514