Introduction to Deep Learning From Logical Calculus to Artificial In
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
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Sandro Skansi
Introduction to Deep Learning From Logical Calculus to Artificial Intelligence
Undergraduate Topics in Computer Science Series editor Ian Mackie Advisory editors Samson Abramsky, University of Oxford, Oxford, UK Chris Hankin, Imperial College London, London, UK Mike Hinchey, University of Limerick, Limerick, Ireland Dexter C. Kozen, Cornell University, Ithaca, USA Andrew Pitts, University of Cambridge, Cambridge, UK Hanne Riis Nielson, Technical University of Denmark, Kongens Lyngby, Denmark Steven S. Skiena, Stony Brook University, Stony Brook, USA Iain Stewart, University of Durham, Durham, UK
Undergraduate Topics in Computer Science (UTiCS) delivers high-quality instructional content for undergraduates studying in all areas of computing and information science. From core foundational and theoretical material to final-year topics and applications, UTiCS books take a fresh, concise, and modern approach and are ideal for self-study or for a one- or two-semester course. The texts are all authored by established experts in their fields, reviewed by an international advisory board, and contain numerous examples and problems. Many include fully worked solutions.
More information about this series at http://www.springer.com/series/7592
Sandro Skansi
Introduction to Deep Learning From Logical Calculus to Artificial Intelligence
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Sandro Skansi University of Zagreb Zagreb Croatia
ISSN 1863-7310 ISSN 2197-1781 (electronic) Undergraduate Topics in Computer Science ISBN 978-3-319-73003-5 ISBN 978-3-319-73004-2 (eBook) https://doi.org/10.1007/978-3-319-73004-2 Library of Congress Control Number: 2017963994 © Springer International Publishing AG, part of Springer Nature 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by 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 and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this 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 or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by the registered company Springer International Publishing AG part
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