DataRobot Blog

Part 2 in a series on the emerging practice of "green AI." In this blog, the focus is on actionable ways AI practitioners can build their models to minimize the cost of Red AI.

Find out how to approach machine learning projects in a sustainable and cost-efficient manner by reassessing the efficiency metrics applies to models.

AI impact assessments are more than black and white compliance documents. Read more about AI Impact Statements - empathy, imperfection, and responsibility.

MMM stands for Marketing Mix Model and it is one of the oldest and most well-established techniques to measure the sales impact of marketing activity statistically. Learn more.

Let’s talk about top three challenges in AI preventing your organization from getting to the next level and understand why they are important.

Although too many stories of embarrassing AI failures are about unfair bias, there’s a more common but less recognized barrier to AI-driven success—many AI systems were not designed for resilience in a world that keeps changing. Learn more.

Every data scientist’s workflow requires visualizing data. Learn how to add interactive components to Zepl Notebooks using JavaScript.

Introducing Alex Tsourmas. Alex works as a Customer-Facing Data Scientist within DataRobot’s Go-To-Market team, as the company continues to build its premier AI platform for organizations across the globe.

With growing pressure on data scientists, every organization needs to ensure that their teams are empowered with the right tools. At the same time, the toolkit needs to meet enterprise needs and regulatory requirements. Data science notebooks have become a crucial part of the data science practice. See the advantages and challenges different notebook solutions bring to the table.