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Mike X Cohen - Practical Linear Algebra for Data Science

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Mike X Cohen Practical Linear Algebra for Data Science
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If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way its presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world modern applications.This practical guide from Mike X Cohen teaches the core concepts of linear algebra as implemented in Python, including how theyre used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, youll be able to understand, implement, and adapt myriad modern analysis methods and algorithms.Ideal for practitioners and students using computer technology and algorithms, this book introduces you toThe interpretations and applications of vectors and matricesMatrix arithmetic (various multiplications and transformations)Independence, rank, and inversesImportant decompositions used in applied linear algebra (including LU and QR)Eigendecomposition and singular value decompositionApplications including least-squares model fitting and principal components analysis

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Practical Linear Algebra for Data Science by Mike X Cohen Copyright 2022 - photo 1
Practical Linear Algebra for Data Science

by Mike X Cohen

Copyright 2022 Syncxpress BV. All rights reserved.

Printed in the United States of America.

Published by OReilly Media, Inc. , 1005 Gravenstein Highway North, Sebastopol, CA 95472.

OReilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://oreilly.com). For more information, contact our corporate/institutional sales department: 800-998-9938 or corporate@oreilly.com .

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  • Illustrator: Kate Dullea
  • September 2022: First Edition
Revision History for the First Edition
  • 2022-09-01: First Release

See https://www.oreilly.com/catalog/errata.csp?isbn=0636920641025 for release details.

The OReilly logo is a registered trademark of OReilly Media, Inc. Practical Linear Algebra for Data Science, the cover image, and related trade dress are trademarks of OReilly Media, Inc.

The views expressed in this work are those of the authors, and do not represent the publishers views. While the publisher and the author have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the author disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights.

978-1-098-12061-0

[LSI]

Preface
Conventions Used in This Book

The following typographical conventions are used in this book:

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Indicates new terms, URLs, email addresses, filenames, and file extensions.

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Used for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords.

Note

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Warning

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Using Code Examples

Supplemental material (code examples, exercises, etc.) is available for download at https://github.com/mikexcohen/LinAlg4DataScience.

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This book is here to help you get your job done. In general, if example code is offered with this book, you may use it in your programs and documentation. You do not need to contact us for permission unless youre reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing examples from OReilly books does require permission. Answering a question by citing this book and quoting example code does not require permission. Incorporating a significant amount of example code from this book into your products documentation does require permission.

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Acknowledgments

I have a confession: I really dislike writing acknolwedgments sections. Its not because I lack gratitude or believe that I have no one to thankquite the opposite: I have too many people to thank, and I dont know where to begin, who to list by name, and who to leave out. Shall I thank my parents for their role in shaping me into the kind of person who wrote this book? Perhaps their parents for shaping my parents? I remember my fourth-grade teacher telling me I should be a writer when I grow up. (I dont remember her name and Im not sure when I will grow up, but perhaps she had some influence on this book.) I wrote most of this book during remote-working trips to the Canary Islands; perhaps I should thank the pilots who flew me there? Or the electricians who installed the wiring at the coworking spaces? Perhaps I should be grateful to zdemir Pasha for his role in popularizing coffee, which both facilitated and distracted me from writing. And lets not forget the farmers who grew the delicious food that sustained me and kept me happy.

You can see where this is going: my fingers did the typing, but it took the entirety and history of human civilization to create me and the environment that allowed me to write this bookand that allowed you to read this book. So, thanks humanity!

But OK, I can also devote one paragraph to a more traditional acknowledgments section. Most importantly, I am grateful to all my students in my live-taught university and summer-school courses, and my Udemy online courses, for trusting me with their education and for motivating me to continue improving my explanations of applied math and other technical topics. I am also grateful for Jess Haberman, the acquisitions editor at OReilly who made first contact to ask if I was interested in writing this book. Shira Evans (development editor), Jonathon Owen (production editor), Elizabeth Oliver (copy editor), Kristen Brown (manager of content services), and two expert technical reviewers were directly instrumental in transforming my keystrokes into the book youre now reading. Im sure this list is incomplete because other people who helped publish this book are unknown to me or because Ive forgotten them due to memory loss at my extreme old age. To anyone reading this who feels they made even an infinitesimal contribution to this book: thank you.

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