Doing Data Science: Straight Talk from the Frontline by Rachel Schutt
My rating: 4 of 5 stars
Doing Data Science is about the practice of data science, not its implementation. It is based on a course on data science that featured a guest lecturer on each topic. This leads to the guest lecturers (and chapters) focusing more on important concepts rather then the methodology. So, this is not a textbook or a how-to-do-this type of book, rather it is a how-to-think-when-doing book.
A problem with books like this where each chapter is written by someone different is the need for coherence. A second is that each author typically has something to day, and she has to say it in her chapter. So, compared to other data science books, it suffers from the chapters not building on each other in a systematic way and having multiple messages that appear as you go through the book.
One benefit from this is that each author has something to say. While I find the book thin on how to do things, this is a good source of wisdom in why things are done and issues that come up along the way in real life. I am teaching data science for the first time and I find myself turning here for topics of discussion which my chosen textbooks don't cover (as they have more focus on how to do things).
I don't think this is the book to use to learn how to do data science, and I suspect the students at Columbia learned how to find other sources to help them figure things out. But it provides wisdom, which is harder to find and worth quite a bit.
Note: I received a free electronic copy of this book from the publisher as par of the OReilly Bloggers program.
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