Janani Narayanan and Karthik Ramasamy share Uber Eats' scaling challenges for nX merchant growth. They detail optimizing retrieval, fixing latency from naive scaling, and root causes in ingestion ...

One of the fundamental challenges of data science has always been finding a way to repeatedly and reliably take a model from creation and put it into production. This can significantly hinder ...

One Model, a platform that uses AI to help employers make decisions about recruiting, hiring, promotions, layoffs and general workplace planning, today announced that it’s raised $41 million in ...

Only 14 percent of organizations are considered “model driven” in deploying data science. Two of five are categorized as “aspiring,” and 46 percent are “laggards.” Just three of 10 ...

Most likely, the assumptions behind your data science model or the patterns in your data did not survive the coronavirus pandemic. Here’s how to address the challenges of model drift The ...

Technology companies are launching data science ... types of data science problems,” she said. “One thing that we struggle with a lot is it’s not simply enough to build a model that ...

By analyzing their distinct strengths and limitations across various data science tasks, you can determine which model best aligns with your specific requirements. From tackling complex coding ...