Quantitative Methods for Data Science: I - Introductory Applied Mathematics

by James Godfrey

This reference book is intended for data scientists and presents introductory applied mathematics appropriate for understanding methodologies used in a variety of disciplines: statistics, engineering and the natural sciences, advanced computing, economics and finance, social media, advertising, climate analysis, healthcare and genetics, and other data-intensive areas. The presentation includes vector and matrix algebra, differential and integral calculus, complex variables, vector calculus, transforms, and ordinary and partial differential equations. The primary objective is to develop tools and techniques for understanding more advanced quantitative methods. The reader is provided an approach that is implementation-driven rather than theoretically-driven. The material is appropriate for college-level applied mathematics courses with an emphasis on data science.

300 pages, Paperback

First published April 24, 2014