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Improving the Zestimate

A Tale of Two Industries: How Programming Languages Differ Between Wealthy and Developing Countries
The latest analysis from Stack Overflow found correlations between certain technologies and GDP per capita. Particularly interesting: questions regarding two data science powerhouses, R and Python, are asked more frequently in high-income countries. - Stack Overflow

Why Are Some New Statistics Embraced and Not Others?
How do you turn data into a baseball stat that not only captures what’s actually happening on the field but also engages the average fan? There are lessons in here about packaging metrics to resonate with your audience— whether they’re up in the stands or across the office. - New York Times Magazine

Python Cheat Sheet for Data Science: Intermediate
A handy reference for Pythonistas who have been around the block a few times. - Dataquest

Practical Data Science for Stats
Many aspects of day-to-day analytics work are missing from the conventional statistics literature and curriculum. This bookmark-worthy collection aims to solve that problem, with tons of preprints on modern analytical workflows. - PeerJ

Train, Score, Repeat, Watch Out! Zillow’s Andrew Martin on modeling pitfalls in a dynamic world.
One of Zillow’s data scientists addresses the challenges that don’t crop up in standard textbook problems or most ML competitions: feedback loops, dynamic datasets, and temporal consistency. A great read for Kagglers and non-Kagglers alike. - No Free Hunch

New from Mode

Data Foundations Nanodegree Program We’re excited to partner with Udacity on this course for those looking to transition into a career in data analysis. Class starts tomorrow. Enroll today! (And see what our CEO has to say about writing the SQL curriculum for this program.)