The advantages of automated machine learning in the front office, the importance of problem framing, and how automated machine learning techniques expand the problem space that can be investigated. Plus, why the choice of machine learning algorithm should be seen as just another parameter to search on.

Introducing DataRobot Pathfinder The potential impact AI will have on the global economy has been estimated to be huge -- about $13 trillion by 2030 (McKinsey). However, even with all the research and media around AI, many executives are still perplexed as to how AI can improve the profitability of their individual organizations. From the difficulties of choosing the right use case to the intricacies of adopting predictions into existing workflows, AI comes with a wide array of challenges that prevent organizations from maximizing the returns on their AI investments.

In these challenging times, parents and students are missing out on summer camps. Kids miss the outdoor activities, camp counselors, and fun projects, and parents miss having their children happy and active. What is a parent to do to make sure their children are engaged in these last weeks of summer time fun? Here comes Varsity Tutors to save the…

“I define nothing. Not beauty, not patriotism. I take each thing as it is, without prior rules about what it should be.” — Bob Dylan It’s entirely possible that someone, somewhere, has successfully built one of the amazing market predicting magic boxes from the previous post in this series, but if so, they’re (sensibly) keeping very quiet about it; the…

At DataRobot, we strongly believe AI is a force for good. From the way deep learning algorithms can create art and writing to its applications for health and medicine, as well as astonishing head-to-head match-ups between AIs and humans in games, AI has made enormous strides towards imitating human behavior. At the same time, we recognize that AI is a…

This series of blog posts is based on a talk the author presented at ODSC Europe 2019 alongside Ayub Hanif, VP at JPMorgan’s Quantitative and Derivatives Strategy. We’ll look at how recent developments in automated machine learning and interpretability can help market participants build, test, and understand powerful AI models that support and enhance their investment processes. But first, some context is needed. Part 1: Beyond the Market-Predicting Magic Box In which we conclude that the existence of this article is strong evidence that we don’t know how to use AI to predict asset prices, either, and try to get real.

AI is Hard Investments in AI are growing every year, even during economic uncertainty. However, there are plenty of obstacles to successfully implementing artificial intelligence projects and creating organizational change that’s needed to drive them.  In such relatively hostile or apathetic climates, AI projects often succeed only because there’s someone who can see the forest for the trees; a person…

DataRobot Intelligent Value Estimator for 2020 MLB Team and Player Performance Recently, we predicted how the 60-game 2020 MLB season would unfold -- for teams and for individual players. Please see our original post for all of the details of how we build the models with DataRobot’s leading artificial intelligence platform. Who is projected to win each division in the…

Epigenetics, the study of how genes express themselves, is a growing field rich with potential. A common metaphor to understand how epigenetics differs from genetics is to think of a human genome as a family recipe book, where your DNA is the recipe. Epigenetics are all of the notes written in the margins making tweaks to the recipe, changing the…