How do you know if your model is going to work? Part 4: Cross-validation techniques

Concluding our guest post series! Authors: John Mount (more articles) and Nina Zumel (more articles). In this article we conclude our four part series on basic model testing. When fitting and selecting models in a data science project, how do you know that your final model is good? And how sure are you that it’s better than the models … Continued

How do you know if your model is going to work? Part 2: In-training set measures

Continuing our guest post series! Authors: John Mount (more articles) and Nina Zumel (more articles). When fitting and selecting models in a data science project, how do you know that your final model is good? And how sure are you that it’s better than the models that you rejected? In this Part 2 of our four part mini-series “How do you … Continued

How do you know if your model is going to work? Part 1: The problem

This month we have a guest post series from our dear friend and advisor, John Mount, on building reliable predictive models. We are honored to share his hard won learnings with the world. Authors: John Mount (more articles) and Nina Zumel (more articles) of Win-Vector LLC. “Essentially, all models are wrong, but some are useful.”George Box Here’s a caricature of a … Continued

Need for Speed: Why Marketing needs to Adapt to High Velocity Data

This holiday retailing season, as customers shopping preferences shift, will you still be marketing to them using stale data?   With the rise of mobile devices, and the “always-on” user, the amount of time spent on the internet has nearly tripled over the last 5 years: 450 billion minutes per month in 2010 to more than 1200 billion … Continued