DataRobot Blog

DataRobot AI Platform is a unique solution that unlocks the full potential of AI for your business. Check out the newest blog post by Dan Wright, CEO at DataRobot.

DataRobot has long believed that to democratize machine learning (ML) on the path to Augmented Intelligence, any user must have seamless access to learning — for example, how to prepare, create, explore, deploy, monitor, and consume ML models. Those already familiar with the DataRobot experience are also familiar with our in-app documentation that makes it easy to keep up with…

Those who watched the vision presentation at the recent AI Experience 2021 event might have noticed that we quietly announced a new MLOps feature called Continuous AI. I want to take some time and drill into this feature in a little more detail. First off, I won’t call it a feature again. Calling something a feature diminishes its value, and…

As they strive to improve models, data scientists continually try new approaches to refine their predictions. To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. This allows data science teams to incorporate any machine learning algorithm or feature engineering method and seamlessly combine them with hundreds of built-in methods. After adding the preferred code,…

As AI has become more ubiquitous, we’ve started to see increasingly more examples of AI behaving badly. Recent high-profile examples include hiring models that are biased against women and facial recognition systems that can’t identify black individuals. At DataRobot, we want to ensure that users have the right tools at their disposal to investigate bias. To meet that goal, we…

Eureqa generates novel, specialized mathematical formulas, much like a physicist would write to describe the laws of nature. Read more about reimagining time-aware modeling with Eureqa.

In several earlier blog posts, we have focused on what we at DataRobot call the AI production gap, which refers to the gap that makes it difficult to transition models from the data science teams who develop them to the IT and DevOps teams who are responsible for deploying and monitoring them in production. Deployment and Monitoring Challenges Our DataRobot…

Datarobot is thrilled to introduce No-Code AI Apps. This allows any user, regardless of their technical expertise, to quickly turn a deployed model into a rich AI application without requiring any coding.

Feature engineering is a critical part of the data science lifecycle that, more often than not, determines the success or failure of an AI project. At DataRobot, we know how hard it is to get started with AI, so we decided to take our automated feature engineering capabilities to the next level. DataRobot's Feature Discovery accelerates feature engineering by generating…