Ebook Neural network and deep learning: A textbook
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Ebook Neural network and deep learning: A textbook
Cham c. Aggarwal •* • • ♦Neural INetworks andDeep Learning• • • . , •A Textbook'SpringerNeural Networks and Deep LearningCham c. AggarwalNeural Networ Ebook Neural network and deep learning: A textbook rks and Deep LearningA TextbookSpringerChant c. AggarwalIBM T. J. Watson Research Center International Business Machines Yorktown Heights, NY, USAISBN 978-3-319-94462-3 ISBN 978-3-3I9-94463-O (eBook)https://doi.Org/l 0.1007/978-3-319-94463-0Library of Congress Control Number: 2018947636(£> Springer Ebook Neural network and deep learning: A textbook International Publishing AG. part of springer Nature 2018This work is subject to copyright. All rights are reserved by the Publisher, whether the wholEbook Neural network and deep learning: A textbook
e or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproducCham c. Aggarwal •* • • ♦Neural INetworks andDeep Learning• • • . , •A Textbook'SpringerNeural Networks and Deep LearningCham c. AggarwalNeural Networ Ebook Neural network and deep learning: A textbook y similar or dissimilar methodology now known or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws a Ebook Neural network and deep learning: A textbook nd regulations and therefore free for general use.The publisher, the authors and the editors are safe to assume that the advice and information in thiEbook Neural network and deep learning: A textbook
s book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express Cham c. Aggarwal •* • • ♦Neural INetworks andDeep Learning• • • . , •A Textbook'SpringerNeural Networks and Deep LearningCham c. AggarwalNeural Networ Ebook Neural network and deep learning: A textbook egard to jurisdictional claims in published maps and institutional affiliations.This Springer imprint is published by the registered company Springer Nature Switzerland AGThe registered company address is: Gcwcrbestrassc 11. 6330 Cham. SwitzerlandTo my wife Lata, my daughter Sayani, and my late pare Ebook Neural network and deep learning: A textbook nts Dr. Prem Sarup and Mrs. Pushplata Aggarwal.Preface‘'Any A.I. smart enough to pass a Turing test is smart enough to know to fail it.”—Ian McDonaldNEbook Neural network and deep learning: A textbook
eural networks were developed to simulate the human nervous system for machine learning tasks by treating the computational units in a learning model Cham c. Aggarwal •* • • ♦Neural INetworks andDeep Learning• • • . , •A Textbook'SpringerNeural Networks and Deep LearningCham c. AggarwalNeural Networ Ebook Neural network and deep learning: A textbook simulates the computations in the human nervous system. This is obviously not a simple task because the computational power of the fastest computer today is a minuscule fraction of the computational power of a human brain. Neural networks were developed soon after the advent of computers in the fif Ebook Neural network and deep learning: A textbook ties and sixties. Rosenblatt's perceptron algorithm was seen as a fundamental cornerstone of neural networks, which caused an initial excitement aboutEbook Neural network and deep learning: A textbook
the prospects of artificial intelligence. However, after the initial euphoria, there was a period of disappointment in which the data hungry and compCham c. Aggarwal •* • • ♦Neural INetworks andDeep Learning• • • . , •A Textbook'SpringerNeural Networks and Deep LearningCham c. AggarwalNeural Networ Ebook Neural network and deep learning: A textbook ilability ami increasing computational power lead to increased successes of neural networks, and this area was reborn under the new label of “deep learning.” Although we are still far from the day that artificial intelligence (Al) is close to human performance, there are specific domains like image Ebook Neural network and deep learning: A textbook recognition, self-driving cars, and game playing, where Al has matched or exceeded human performance. It is also hard to predict what Al might be ableEbook Neural network and deep learning: A textbook
to do in the future. For example, few computer vision experts would have thought two decades ago that any automated system could ever perform an intuCham c. Aggarwal •* • • ♦Neural INetworks andDeep Learning• • • . , •A Textbook'SpringerNeural Networks and Deep LearningCham c. AggarwalNeural Networ Ebook Neural network and deep learning: A textbook h sufficient training data, and some variants like recurrent neural networks are known to be Turing complete. Turing completeness refers to the fact that a neural network can simulate any learning algorithm, given sufficient training data. The sticking point is that the amount of data required to le Ebook Neural network and deep learning: A textbook arn even simple tasks Ls often extraordinarily large, which causes a corresponding increase in training time (if we assume that enough training data iEbook Neural network and deep learning: A textbook
s available in the first place). For example, the training time for image recognition, which is a simple task for a human, can be on the order of weekCham c. Aggarwal •* • • ♦Neural INetworks andDeep Learning• • • . , •A Textbook'SpringerNeural Networks and Deep LearningCham c. AggarwalNeural Networ Ebook Neural network and deep learning: A textbook resolved even today. Nevertheless, given that the speed of computers isVIICham c. Aggarwal •* • • ♦Neural INetworks andDeep Learning• • • . , •A Textbook'SpringerNeural Networks and Deep LearningCham c. AggarwalNeural NetworGọi ngay
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