I'm an accountant but work consulting as a data/software "engineer" (or in those roles). For a while I got excited by all the "data science" books, until I admitted to myself 2 years ago that without the Math & Stats background, I'm wasting my time.<p>I went back to varsity (part time) this year, studying Applied Maths and Stats. Even with the basics that I now know, going through this book; I can feel that a glass ceiling is broken.<p>I'm going to print it bit by bit, and study its contents (after my exams). Thanks!
Not to be confused with, "The Foundations of Data Science", a free textbook used/created for UC Berkeley's data science course:<p><a href="https://www.inferentialthinking.com/" rel="nofollow">https://www.inferentialthinking.com/</a>
Looks like this book heavily intersects with "Probability and Computing: Randomization and Probabilistic Techniques in Algorithms and Data Analysis" by Mitzenmacher/Upfal [0].<p>[0] <a href="https://books.google.com/books?id=E9UlDwAAQBAJ&pg=PA1&source=kp_read_button#v=onepage&q&f=false" rel="nofollow">https://books.google.com/books?id=E9UlDwAAQBAJ&pg=PA1&source...</a>
Ravindran Kannan, one of the authors taught a course of the same name at CSA, IISc. The video lectures of the course are available here: <a href="http://drona.csa.iisc.ernet.in/~chiru/datascience/iisclectures.html" rel="nofollow">http://drona.csa.iisc.ernet.in/~chiru/datascience/iisclectur...</a>
I always thought linear regression was a “foundation” of this field, but there is no discussion of a technique by this name in this book. Is there another name it goes by?
I also recommend ISLR
<a href="http://www-bcf.usc.edu/~gareth/ISL/" rel="nofollow">http://www-bcf.usc.edu/~gareth/ISL/</a>