| Introduction to Deep Learning (MIT Press) |
| Monday, 11 February 2019 | |||
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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. Author Eugene Charniak, 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. The book illustrates the basics of deep learning by working through programs in the Tensorflow open-source machine learning framework . Author: Eugene Charniak
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