For those who know, How does this book differ from Foundations of Data Science by Blum/Hopcroft/Kannan ?
http://www.cs.cornell.edu/jeh/book%20June%2014,%202017pdf.pd... ?
http://www.cs.cornell.edu/jeh/book%20June%2014,%202017pdf.pd... ?
CASI looks very cutting edge, but also covers the origins of the use of computers for statistical methods. So this covers how computers can and have been used to do statistics.
FoDS looks like a very thorough data science book. Less of a "then VS now" book and more of a collection of what you need as a data scientist.
In CASI, I like the chapter on FDR, a very important topic not found in FoDS (?!). FDR is critical for correcting for multiple testing, seems essential for data science but maybe the authors consider it cutting edge and not foundational. However, the wavelet chapter in FoDS makes me happy, a very useful topic for series data.
Both great books, thanks for the links!