How Airbnb Solved the Bizarre Problem of Too Many Positive Reviews

Laura Montini wrote an article for Inc. about my talk last week at the Import.io Data summit. The piece provides a nice summary of the contents of the talk – the work we are doing at Airbnb to improve the informativeness of reviews through experiments. Read the article here.

Introduction to Data Science with Udacity

Today, the the course I am teaching along with Udacity, “Introduction to Data Science,” launched. The course covers the basic skills most data scientists have (data acquisition and munging, data analysis, data visualization, and big data techniques). The course is anchored by a project wherein students interact with data from the New York City MTA Subway system.

The course can be found here.

TrialPay Offer Similarity

I just published my first post to the TrialPay Enginerds Blog.  The post details some work I’ve done to categorize offers from TrialPay’s advertisement network as “similar,” and identify “communities” of offers.  There’s also a neat visualization of an adjacency matrix, which I built using d3.js.  The visualization is an adaptation of some work done by Mike Bostock.

The full post can be found here.

Honey Badger Softball Stats I

TrialPay’s softball team, the Honey Badgers, began our season last Wednesday.  In addition to playing, I’ve decided to make myself the team statistician.  Drawing some inspiration from the JHU physics graduate student intramural softball team, I thought it would be fun to keep a running tabulation of players’ lifetime statistics.  In order to keep it manageable and given that I’m also playing, I’ve limited myself to basic offensive and pitching statistics. 

The box score from our first game can be found below the jump.

  1 2 3 4 5 R H E  
TrialPay Honey Badgers 2 3 1 8 4 18 15 4  
Survey Monkey 0 0 0 3 0 3 6 0

 

Continue reading “Honey Badger Softball Stats I”