From Vin Vashishta discussing the implosion over at Zillow: For Data Scientists, there are several lessons. You’d better understand the science before taking on significant projects. When revenue starts getting booked against Machine Learning projects, model reliability is critical. Research methodology is essential. When revenue growth starts being built around Machine Learning capabilities, those capabilities need to be comprehensive. The body of evidence supporting core models needs to be substantial.
Kieran Healy created a really interesting analogy to the wealth gap in the US: So, what if the space on the plane was allocated in proportion to the share of total income earned by each class? With a bit of help from the Census Bureau, Emmanuel Saez, and the Federal Aviation Authority, Air Gini is proud to bring you the future of air travel