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Analytics Dispatch 7/31/2017

Facebook's AI factory

Using Machine Learning to Predict Value of Homes On Airbnb
How Airbnb used internal and open-source tools (like Python!) to lower the overall development costs of customer lifetime value (LTV) modeling. Code examples abound. - Airbnb Engineering and Data Science

What's so hard about histograms?
You'll never again accept the default bin sizes in a visualization tool once you've explored this interactive guide to all the decisions that go into building a histogram. - Aran Lunzer & Amelia McNamara

Inside Facebook's AI Workshop
When Joaquin Candela first started at Facebook, he worked on an ad-targeting algorithm with a handful of engineers. Five years later, he runs the Applied Machine Learning team, which comprises hundreds of employees running thousands of experiments a day. Here's how he scaled up Facebook's AI factory at breakneck speed. - Harvard Business Review

Explaining the Gap: Visualizing One’s Predictions Improves Recall and Comprehension of Data
Something to take into consideration for your next data viz design: this study found that asking people to predict the trend of a line on a chart helps them to better remember the data in the long-run. - UW Interactive Data Lab

Technical Debt in Machine Learning
What do feedback loops, correction cascades, and hobo-features have in common? They're all machine learning anti-patterns that can slowly creep into your infrastructure and create a ticking time bomb. - Towards Data Science

New from Mode

WrangleConf 2017: Facing bias, ethical obligation, and your audience
Got serious FOMO from looking at the #WrangleConf Twitter feed? Don't worry, we've got a rundown of the best talks on data science ethics from industry leaders like Trey Causey and Sean Taylor.

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