DataRobot Blog

Google recently started promoting automated machine learning (what they call AutoML) - something that DataRobot customers have been doing for years. So what is driving Google to now embrace this transformative approach? Guest blogger Damian Mingle explains.  You might be asking yourself why Google, a company with over $600 billion in market cap, is rethinking its business, and if it…

This is part 1 of a series of blog posts detailing the development of the Relationships by DataRobot web app. Background A colleague of mine did a talk not too long ago about a Stanford study called How Couples Meet and Stay Together. The study was done by Michael Rosenfeld, a sociology professor who studies, among many other things, how the…

This is part 2 of a series of blog posts detailing the development of the Relationships by DataRobot web app.  Here’s Part 1. The starting blocks As with any new project, particularly when someone else built the datasets, there’s going to be a bit of learning curve figuring out what they did and getting it into the right shape for…

This is part 3 of a series of blog posts detailing the development of the Relationships by DataRobot web app.  Here are Parts 1 and Parts 2. Preliminary Notes on Optimization Criteria There are many different reasons to build a predictive model. In some cases, predictive accuracy is the number one priority; i.e., getting predictions that are more accurate than…

This is part 4 of a series of blog posts detailing the development of the Relationships by DataRobot web app.  Here are Parts 1, Parts 2, and Parts 3.  Overview & Purpose Our mission from the start was to build a simple quiz (web application) that any couple could use to determine if their relationship would last two or more years.…

Kobe Bryant took a lot of shots in his career - 30,699 to be precise (regular season and playoffs combined), second-most in NBA history and nearly 2,000 more than Michael Jordan did in his legendary career. Data for each of these shots is publicly available from NBA.com, but analyzing all thirty thousand shots to find insights and trends from Kobe…

The insurance industry is among the most sophisticated in terms of analytics, having pioneered some of the most advanced stats and modeling techniques more than a hundred years ago. Even so, machine learning in insurance is still changing the game today, giving the most innovative companies a huge leg up on the competition. Here are three practical ways that the insurance…

As our world experiences massive transformation, it’s easy to get caught up in the buzz about AI, autonomous vehicles, robots and drones. But amid all the noise, it’s worth remembering that one of the core aspects of company success is its people and thriving values-driven culture. We don't hesitate to say:  It’s our values that have led Paxata to make…

“Underpinning many published scientific conclusions is the concept of ‘statistical significance,’ typically assessed with an index called the p-value. While the p-value can be a useful statistical measure, it is commonly misused and misinterpreted.”  ASA Statement on Statistical Significance and p-Values If you’ve ever heard the words “statistically significant” or “fail to reject,” then you are among the countless thousands…