Matthew Kirk - Thoughtful Machine Learning with Python: A Test-Driven Approach
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Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext.
Featuring graphs and highlighted code examples throughout, the book features tests with Pythons Numpy, Pandas, Scikit-Learn, and SciPy data science libraries. If youre a software engineer or business analyst interested in data science, this book will help you:
- Reference real-world examples to test each algorithm through engaging, hands-on exercises
- Apply test-driven development (TDD) to write and run tests before you start coding
- Explore techniques for improving your machine-learning models with data extraction and feature development
- Watch out for the risks of machine learning, such as underfitting or overfitting data
- Work with K-Nearest Neighbors, neural networks, clustering, and other algorithms
Matthew Kirk: author's other books
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![Frank Kane [Frank Kane] - Hands-On Data Science and Python Machine Learning](/uploads/posts/book/119615/thumbs/frank-kane-frank-kane-hands-on-data-science-and.jpg)
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A Test-Driven Approach
Matthew Kirk
by Matthew Kirk
Copyright 2017 Matthew Kirk. 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/safari). For more information, contact our corporate/institutional sales department: 800-998-9938 or corporate@oreilly.com .
- Editors: Mike Loukides and Shannon Cutt
- Production Editor: Nicholas Adams
- Copyeditor: James Fraleigh
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- Interior Designer: David Futato
- Cover Designer: Randy Comer
- Illustrator: Rebecca Demarest
- January 2017: First Edition
- 2017-01-10: First Release
See http://oreilly.com/catalog/errata.csp?isbn=9781491924136 for release details.
The OReilly logo is a registered trademark of OReilly Media, Inc. Thoughtful Machine Learning with Python, the cover image, and related trade dress are trademarks of OReilly Media, Inc.
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.
978-1-491-92413-6
[LSI]
I wrote the first edition of Thoughtful Machine Learning out of frustration over my coworkers lack of discipline. Back in 2009 I was working on lots of machine learning projects and found that as soon as we introduced support vector machines, neural nets, or anything else, all of a sudden common coding practice just went out the window .
Thoughtful Machine Learning was my response. At the time I was writing 100% of my code in Ruby and wrote this book for that language. Well, as you can imagine, that was a tough challenge, and Im excited to present a new edition of this book rewritten for Python. I have gone through most of the chapters, changed the examples, and made it much more up to date and useful for people who will write machine learning code. I hope you enjoy it.
As I stated in the first edition, my door is always open. If you want to talk to me for any reason, feel free to drop me a line at matt@matthewkirk.com. And if you ever make it to Seattle, I would love to meet you over coffee.
The following typographical conventions are used in this book:
Constant widthConstant width boldConstant width italicThis element signifies a general note.
Supplemental material (code examples, exercises, etc.) is available for download at http://github.com/thoughtfulml/examples-in-python.
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 a CD-ROM of 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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Ive waited over a year to finish this book. My diagnosis of testicular cancer and the sudden death of my dad forced me take a step back and reflect before I could come to grips with writing again. Even though it took longer than I estimated, Im quite pleased with the result.
I am grateful for the support I received in writing this book: everybody who helped me at OReilly and with writing the book. Shannon Cutt, my editor, who was a rock and consistently uplifting. Liz Rush, the sole technical reviewer who was able to make it through the process with me. Stephen Elston, who gave helpful feedback. Mike Loukides, for humoring my idea and letting it grow into two published books.
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