Foundations of Data Science

While traditional areas of computer science remain highly important, increasingly re- searchers of the future will be involved with using computers to understand and extract usable information from massive data arising in applications, not just how to make com- puters useful on specific well-defined problems. With this in mind we have written this book to cover the theory likely to be useful in the next 40 years, just as an understanding of automata theory, algorithms and related topics gave students an advantage in the last 40 years. One of the major changes is the switch from discrete mathematics to more of an emphasis on probability, statistics, and numerical methods.

 

Foundations of Data Science
by Avrim Blum (CMU), John Hopcroft (Cornell), and Ravindran Kannan (MSR) 
June 2016
Available at https://www.cs.cornell.edu/jeh/book2016June9.pdf

Source: www.cs.cornell.edu

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