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Calculus not required (plus big news from Mode!)

SKIP THE CALC
The real prerequisite for machine learning isn’t math, it’s data analysis
Machine learning amateurs, take heart. Proficiency with high level math may be essential for machine learning theory. But with out-of-the-box tools like R’s gmodels package or Python’s scikit-learn library, you don’t need to know linear algebra or calculus to build a successful predictive model. You do, however, need to know your way around a dataset. - Sharp Sight Labs

HOLE IN ONE
Golfers Join the Rest of World, Use Data
Decades after baseball front offices started using data to win games, some golfers are now turning to data to find ways to improve performance and devise course strategy. - The Wall Street Journal

BY THE DOZEN
One Chart, Twelve Tools & One Chart, Twelve Charting Libraries
Most data practitioners have a favorite data visualization tool—whether it’s ggplot, Seaborn, or good old-fashioned Excel. But for a beginner, the range of options can be overwhelming. These two posts explore 24 tools and libraries for creating the same bubble chart, complete with code. - Lisa Charlotte Rost

Q&As
[PODCAST] Statistically Interesting
Craving a new data science podcast? Check out Statistically Interesting, a series of interviews with data science leaders at companies like Twitch, Vimeo, and Weebly. - Statistically Interesting

People are talking about: SF rental data

When someone mentions San Francisco’s housing shortage, they usually cite a limited dataset containing San Francisco Chronicle rental listings from 1979-2001. Eric Fischer took it upon himself to collect and analyze decades of new information by transcribing Chronicle rental ads from 1948-1979 and Craigslist rental listings from 2001 onward (and put it on Github).

What's goin' on Big news at Mode

Today we’ve got three exciting pieces of news to share (you can read the full announcement here):

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