Data Science from Scratch: First Principles with Python 2nd Edition
Preface to the Second Edition
I am exceptionally proud of the first edition of Data Science from Scratch. It turned out very much the book I wanted it to be. But several years of developments in data science, of progress in the Python ecosystem, and of personal growth as a developer and educator have changed what I think a first book in data science should look like.
In life, there are no do-overs. In writing, however, there are second editions.
Accordingly, I’ve rewritten all the code and examples using Python 3.6 (and many of its newly introduced features, like type annotations). I’ve woven into the book an emphasis on writing clean code. I’ve replaced some of the first edition’s toy examples with more realistic ones using “real” datasets. I’ve added new material on topics such as deep learning, statistics, and natural language processing, corresponding to things that today’s data scientists are likely to be working with. (I’ve also removed some material that seems less relevant.) And I’ve gone over the book with a fine-toothed comb, fixing bugs, rewriting explanations that are less clear than they could be, and freshening up some of the jokes.
The first edition was a great book, and this edition is even better. Enjoy!
- Joel Grus
- Seattle, WA
Conventions Used in This Book
The following typographical conventions are used in this book:
- Indicates new terms, URLs, email addresses, filenames, and file extensions.
- 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.
Constant width bold
- Shows commands or other text that should be typed literally by the user.
Constant width italic
- Shows text that should be replaced with user-supplied values or by values determined by context.
This element signifies a tip or suggestion.
This element signifies a general note.
This element indicates a warning or caution.
Using Code Examples
Supplemental material (code examples, exercises, etc.) is available for download at https://github.com/joelgrus/data-science-from-scratch.
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 you’re 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 O’Reilly 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 product’s documentation does require permission.
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