How to Structure Your Code for Machine Learning Development
A highly overlooked yet critical skill for data scientists.
Machine Learning
60 articles
Formulating and Implementing the t-SNE Algorithm From Scratch
The most extensive visual guide to never forget how t-SNE works.
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.
