AI is now mature and widespread enough to encounter criticism. Since most AI systems today aren’t quite software, the difference in their business model renders them less attractive for venture capitalists.

Although feature stores play a vital role in data strategy, it’s still difficult to find information about them online. But understanding what feature stores are and why they’re important is crucial, especially in today’s world of increasing data governance, and business problems being increasingly solved by machine learning models.

A Game-Plan to Scaling in a Responsible Way. Scaling up your platform is a necessary part of the evolution of your company. Moreover, scaling should be something that’s always on your mind.

How to deal with scaling on a day-to-day basis. You’re now managing a scaled system. Congratulations! But wait—don’t throw your feet up just yet.

Are you interested in getting into the field of data science? We don’t blame you. Data science is an exciting field that’s constantly changing and developing, which gives data scientists’ work endless potential.

Imbalanced classes are a common problem in machine learning classification, where there’s a disproportionate ratio of observations in each class. In this article, we offer guidelines for working with imbalanced datasets.

A/B testing is usually the first choice for people aiming to optimize an ad campaign setup. Instead of relying on guesswork, with A/B testing you can make choices based on more scientific data. 

While heatmaps are hardly a new concept in digital advertising, their advantages are often forgotten and they’re rarely used for in-app user acquisition. In this article, we survey some of the ways in which heatmaps can be beneficial to your performance strategy.

In order to ensure that the work of data scientists is well-managed and delivers impactful results, our approach focuses on defining a set of possible outcomes for each data science task.