Statistics

and managing products, it’s crucial to make sure they’re performing as expected and that the whole lot is running easily. We typically depend on metrics to gauge the health of our products. And...

A previous article provided a of conceptual frameworks – analytical structures for representing abstract concepts and organizing data. Data scientists use such frameworks in a wide range of contexts, from use case ideation and...

discussed about classification metrics like ROC-AUC and Kolmogorov-Smirnov (KS) Statistic in previous blogs. On this blog, we are going to explore one other vital classification metric called the Gini Coefficient. Why do we've multiple classification...

In a seminal but underappreciated book titled , Marcus Hutter attempted a mathematical formulation of universal artificial intelligence, shortened to AIXI. This text goals to make AIXI accessible to data scientists, technical enthusiasts and...

To get essentially the most out of this tutorial, you must have a solid understanding of the right way to compare two distributions. For those who don’t, I like to recommend testing this excellent...

in a sentence provide numerous information, corresponding to what they mean in the true world, how they hook up with other words, how they alter the meaning of other words, and sometimes their...

What Are Random Effects and Fixed Effects? When designing a study, we frequently aim to isolate independent variables from those of no interest to watch their true effects on the dependent variables. For instance, let’s...

make smart decisions when it starts out knowing nothing and may only learn through trial and error? This is strictly what one in all the best but most vital models in reinforcement learning is...