Although normal distributions are the most commonly used, a lot of real-world data unfortunately is not normal. When faced with extremely skewed data, it’s tempting for us to utilize log…

The subjective details holding together one of economics’ favourite models

A theoretical and practical introduction to non-parametric density estimation.

A generalized version of Kaplan-Meier allows to model a continuous value (like money) instead of a binary signal (like survival)

Mastering the fundamentals of bagging and boosting with simple examples

A journey into three intuitions: Common, Bayesian and Causal

A breakdown of the three fundamental math fields required for machine learning: statistics, linear algebra, and calculus.

Using Python to determine where NBA coaches come from and what makes them successful

Using one model to personalize ML results

These common, basic statistics and machine learning concepts are crucial for landing a data scientist role