Essential math for Data Scientists explained from scratch — Moments are set of statistical parameters used to describe a distribution. The calculations are simple, so are often used as a first quantitative insight into the data. A good understanding of data should always be the step before training any advanced ML model. …

Clearly explained theory with handy functions in R and Python — You know that probability distributions are important and that binomial distribution is a basic one. But you still have some doubts about it. When should I use it? How to understand equations for probability mass function and cumulative density function? What are the handy functions in R and Python? In…

An automated way to set the path and create an output folder — My codes used to be mine in Academia. We discussed the methodology of both experiments and data analysis. Trying to understand the results and phenomena behind them took us long hours. But I did not need to share my codes. Things changed when I moved to the financial market. It…

Essential math for Data Scientists explained from scratch — Matrices are commonly used in many areas, such as physics, graphics, risk modeling, and statistics. Getting familiar with matrices and their transformations is relatively easy but crucial to understanding data science concepts, including linear regression. So let’s dive into it! The article is divided into two parts: I. Math Refresher II. Related…