Data Science from Scratch. First Principles with Python

Data Science from Scratch. First Principles with Python at Python.Engineering

Data Science from Scratch. First Principles with Python

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Data scientist has been called “the sexiest job of the 21st century,” presumably by someone who has never visited a fire station. Nonetheless, data science is a hot and growing field, and it doesn’t take a great deal of sleuthing to find analysts breathlessly prognosticating that over the next 10 years, we’ll need billions and billions more data scientists than we currently have.

485 pages, published in 2019
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
Joel Grus

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