Problem Knowledge Acquisition
The logical step after defining the business problem and organizing the project is to collect the available internal (inside the business) and external (in publicly available references) information about the topic. Problem knowledge acquisition and organ
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Applying Data Science How to Create Value with Artificial Intelligence
Applying Data Science
Arthur K. Kordon
Applying Data Science How to Create Value with Artificial Intelligence
Arthur K. Kordon CEO, Kordon Consulting LLC Fort Lauderdale, FL, USA
ISBN 978-3-030-36374-1 ISBN 978-3-030-36375-8 https://doi.org/10.1007/978-3-030-36375-8
(eBook)
© Springer Nature Switzerland AG 2020 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, expressed 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. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
To my Teachers
Preface
Artificial Intelligence is no match for natural stupidity. Anonymous
Like it or not, artificial intelligence (AI) has invaded our lives like a storm. Some are thrilled by the new opportunities this magical technology may open up. Others are scared for their jobs, expecting the invasion of the robots. Most of us, especially those in the business, are confused by the AI hype and concerned about losing our competitive edge. A package of new buzzwords, such as big data, advanced analytics, and the Internet of Things (IoT), under the rising scientific star of Data Science are contributing to the growing level of confusion. Often the confusion leads to a mess after incompetent attempts to push this technology without the needed infrastructure and skillset. Unfortunately, the results are disappointing and the soil is poisoned for future applications for a long period of time. Handling the confusion and navigating businesses through this maze of new technologies and buzzwords related to AI is a well-identified need in the business world. Business practitioners and even academics are not very familiar with the capabilities of Data Science as a research discipline, linked to AI. Another issue is that the hype about AI in the media is not supported w
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