- Paperback: 330 pages
- Publisher: O'Reilly Media; 1 edition (April 30, 2015)
- Language: English
- ISBN-10: 149190142X
- ISBN-13: 978-1491901427
- Product Dimensions: 7 x 0.7 x 9.2 inches
- Shipping Weight: 1.1 pounds (View shipping rates and policies)
- Average Customer Review: 88 customer reviews
- Amazon Best Sellers Rank: #6,641 in Books (See Top 100 in Books)
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Data Science from Scratch: First Principles with Python 1st Edition
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About the Author
Joel Grus is a software engineer at Google. Before that he worked as a data scientist at multiple startups. He lives in Seattle, where he regularly attends data science happy hours. He blogs infrequently at joelgrus.com.
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Top customer reviews
It's the right size and correct coverage for the content and the author's sense of humor (indeed, that of a data scientist) resonates with the audience.
Solid introduction, even better review or brief explanation of commonly encountered topics.
One of the best O'Reilly books I've read in a long time-- in fact, a technical book at the level I used to expect from O'Reilly.
This is a very basic book on Data Science but it gives a broad overview which helps you get a perspective on the tools that are available. This book teaches methods by developing actual code for these methods. You will find in work situations that you will use library functions instead of "rolling your own" but this book helps bring the details together by having you actually code these techniques. I support this approach 100% Once you have this overview, you can drill down into specifics with other materials like textbooks or cookbooks.
I'd did flinch at some of the explanations in this book but it really is a "from Scratch" approach and some things are simplified to avoid distractions.
This book also teaches basic Python 2.7 with a quick start chapter, so it is self contained for any scientist or engineer that wants to get started adding Data Science techniques to their repertoire.
As the "from Scratch" in the title implies, the objective of this book is to teach the fundamental ideas and techniques of data science from first (or nearly first) principles. After working through this book, you'll be better able to meaningfully utilize the pre-packaged software (whether it's Matlab, R, scikit-learn, or whatever) that you will use in "real life".
And although the knowledge you'll gain is largely independent of the programming language, you will as a bonus learn from the clear and elegant python code included. Every key topic, from probability, statistics, and other mathematical subjects, to machine learning and databases, is covered in a crystal clear manner.
In summary, this book is the bee's knees.
Most recent customer reviews
Rather, it introduces the machinery of data science with simple...Read more