Formulating the Principal Component Analysis (PCA) Algorithm From Scratch
Approaching PCA as an optimization problem.
Generalized Linear Models (GLMs): The Supercharged Linear Regression
The limitations of linear regression and how GLMs solve them.
Bayesian Optimization for Hyperparameter Tuning
The caveats of grid search and random search and how Bayesian optimization addresses them.
Why Do We Use Sigmoid in Logistic Regression?
The origin of the Sigmoid function and a guide on modeling classification datasets.
Develop an Elegant Testing Framework For Data Science Projects Using Pytest
A Comprehensive Guide to Pytest for data scientists.
Where Did The Assumptions of Linear Regression Originate From?
The most extensive and in-depth guide to linear regression.
