DataRobot Blog

See the examples of everything involved in the modeling process, along with highlights of the automation built into the DataRobot platform that get you up and running with ML.

So far in this series, we’ve discussed how the securities industry would use AI in general (part one), compared machine learning in the front office to “traditional” quant (part two), and described how automated machine learning in particular can bring enormous power and efficiency gains to the quantitative investment process (part three). In this installment, we’ll describe our recommendations for…

Learn what target leakage is and how to detect it to ensure that projects follow data science best practices and resulting models will be robust to real-world data.

Staying in tune with consumer demands can be challenging, especially when these demands change almost daily. Tracking consumption patterns to predict demand is a monumental task. Previously, solving this problem involved spreadsheets or legacy statistical methods. But with automation and machine learning, artificial intelligence can help organizations slice through mounds of data to get more accurate and timely insights on consumer demand . Machine learning can build forecasts for hundreds of thousands of items and consider all of the minute details for each one of them, from seasonality to sales history. For example, automated machine learning can easily create separate models on clusters of products, using unsupervised ML techniques, to make predictions even more granular such as by store, week, and SKU.

This year's 72nd Primetime Emmy Awards will take place on Sunday, September 20th. Looking back at last year's post where we used DataRobot to predict the winners for the 2019 Primetime Emmy Awards for the "Outstanding Drama Series" and "Outstanding Comedy Series" categories, we correctly predicted Game Of Thrones winning Outstanding Drama Series but missed the mark on Outstanding Comedy Series (Fleabag was the winner, whereas we predicted Veep would take the top prize). Since Game Of Thrones is absent from this year's 2020 Emmy nominations, let's see if the data says anything about potential underdog winners!

Humble AI is a new feature in DataRobot that protects the quality of your predictions in situations where the model may be less confident. With Humble AI, users create rules for models in deployment for predictions made in real-time. These rules identify conditions that indicate quantifiably that a prediction may be unsure, and then can trigger actions like defaulting to…

This article was originally published at Algorithimia’s website. The company was acquired by DataRobot in 2021. This article may not be entirely up-to-date or refer to products and offerings no longer in existence. Find out more about DataRobot MLOps here. A machine learning framework is an interface that allows developers to build and deploy machine learning models faster and easier.…

This article was originally published at Algorithimia’s website. The company was acquired by DataRobot in 2021. This article may not be entirely up-to-date or refer to products and offerings no longer in existence. Find out more about DataRobot MLOps here. AI/ML model governance is the overall process for how an organization controls access, implements policy, and tracks activity for models.…

This article was originally published at Algorithimia’s website. The company was acquired by DataRobot in 2021. This article may not be entirely up-to-date or refer to products and offerings no longer in existence. Find out more about DataRobot MLOps here. Learn all about machine learning pipelines, how they benefit an organization, and how you can implement this technology in your…