The Big R-Book. Philippe J. S. De Brouwer
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THE BIG R-BOOK
FROM DATA SCIENCE TO LEARNING MACHINES AND BIG DATA
Philippe J.S. De Brouwer
This edition first published 2021
© 2021 John Wiley & Sons, Inc.
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The right of Philippe J.S. De Brouwer to be identified as the author of this work has been asserted in accordance with law.
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Library of Congress Cataloging-in-Publication Data
Names: De Brouwer, Philippe J. S., author.
Title: The big R-book : from data science to learning machines and big data / Philippe J.S. De Brouwer.
Description: Hoboken, NJ, USA : Wiley, 2020. | Includes bibliographical references and index.
Identifiers: LCCN 2019057557 (print) | LCCN 2019057558 (ebook) | ISBN 9781119632726 (hardback) | ISBN 9781119632764 (adobe pdf) | ISBN 9781119632771 (epub)
Subjects: LCSH: R (Computer program language)
Classification: LCC QA76.73.R3 .D43 2020 (print) | LCC QA76.73.R3 (ebook) | DDC 005.13/3–dc23
LC record available at https://lccn.loc.gov/2019057557
LC ebook record available at https://lccn.loc.gov/2019057558
Cover Design: Wiley
Cover Images: Information Tide series and Particle Geometry series
© agsandrew/Shutterstock, Abstract geometric landscape © gremlin/Getty Images, 3D illustration Rendering © MR.Cole_Photographer/Getty Images
To Joanna, Amelia and Maximilian
Foreword
This book brings together skills and knowledge that can help to boost your career. It is an excellent tool for people working as database manager, data scientist, quant, modeller, statistician, analyst and more, who are knowledgeable about certain topics, but want to widen their horizon and understand what the others in this list do. A wider understanding means that we can do our job better and eventually open doors to new or enhanced careers.
The student who graduated froma science, technology, engineering ormathematics or similar program will find that this book helps to make a successful step from the academic world into a any private or governmental company.
This book uses the popular (and free) software R as leitmotif to build up essential programming proficiency, understand databases, collect data, wrangle data, buildmodels and select models froma suit of possibilities such linear regression, logistic regression, neural networks, decision trees, multi criteria decision models, etc. and ultimately evaluate a model and report on it.
We will go the extra mile by explaining some essentials of accounting in order to build up to pricing of assets such as bonds, equities and options. This helps to deepen the understanding how a company functions, is useful to bemore result oriented in a private company, helps for one's own investments, and provides a good example of the theories mentioned before. We also spend time