Description: Deep Learning: Adaptive Computation and Machine Learning Series - 1 Day Ship Condition of textbook is authentic, sealed, with very minor wear to cover. Clean pages, no marks or writing Ships secure USPS Ground for Free within 24 Hours. An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. Deep Learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Price: 31.45 USD
Location: Douglasville, Georgia
End Time: 2024-10-30T19:59:47.000Z
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Restocking Fee: No
Return shipping will be paid by: Seller
All returns accepted: Returns Accepted
Item must be returned within: 60 Days
Refund will be given as: Money Back
Number of Pages: 800 Pages
Publication Name: Deep Learning
Language: English
Publisher: MIT Press
Item Height: 1.3 in
Publication Year: 2016
Subject: Intelligence (Ai) & Semantics, Computer Science
Item Weight: 45.5 Oz
Type: Textbook
Subject Area: Computers
Author: Yoshua Bengio, Ian Goodfellow, Aaron Courville
Item Length: 9.3 in
Item Width: 7.3 in
Series: Adaptive Computation and Machine Learning Ser.
Format: Hardcover