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Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence
Paperback
Series: Undergraduate Topics in Computer Science
DatabasesGeneral ComputersGeneral Mathematics
ISBN13: 9783319730035
Publisher: Springer Nature
Published: Feb 15 2018
Pages: 191
Weight: 0.66
Height: 0.44 Width: 6.14 Depth: 9.21
Language: English
This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner. The content coverage includes convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks and autoencoders. Numerous examples in working Python code are provided throughout the book, and the code is also supplied separately at an accompanying website.
This clearly written and lively primer on deep learning is essential reading for graduate and advanced undergraduate students of computer science, cognitive science and mathematics, as well as fields such as linguistics, logic, philosophy, and psychology.
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