-
Multiclass Classification with SVM
Learn how Support Vector Machines extend to multiclass classification with an intuitive breakdown of margin concepts, loss derivation, and the multiclass hinge loss formulation.
-
Multiclass Logistic Regression & Multiclass Perceptron Algorithm
Learn the essentials of multiclass classification, focusing on logistic regression, perceptron algorithms, and efficient model building techniques.
-
Multiclass Classification - Overview
Learn how One-vs-All and One-vs-One extend binary classification to multiclass problems, their key differences, and best use cases.
-
Gaussian Regression - A Bayesian Approach to Linear Regression
This guide explores Gaussian regression, deriving its closed-form posterior, linking MAP estimation to ridge regression, and explaining predictive uncertainty for Bayesian inference.
-
My Understanding of "Efficient Algorithms for Online Decision Problems" Paper
A breakdown of Follow the Perturbed Leader (FPL) from Kalai & Vempala’s (2005) paper, "Efficient Algorithms for Online Decision Problems." This blog explores how FPL improves online decision-making, minimizes regret, and extends to structured problems like shortest paths and adaptive Huffman coding.