Five books every data scientist should read that are not about data science

I wrote my first line of R code in 2010 for a class at the University of Washington (UW). I was hooked once I realized how much more powerful coding is than spreadsheets. Over the past decade, I witnessed the term ‘data science’ come into widespread use and saw the rise and fall of buzzwords like big data, business intelligence, analytics, and now artificial intelligence.

My class at UW was ‘computational finance,’ which easily filled a sizable lecture hall the way deep learning classes do today. At the time, the financial crisis was fresh in everyone’s mind. So was the, not to subtle, message for engineers; if you want to get a well paying job, go into finance and become a quant, much like data science today.

Author: Isaac Faber

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