all articles

K-Means

The article provides a comprehensive guide to implementing the K-Means clustering algorithm from scratch, exploring its functionality, optimization, and hyperparameter tuning, and compares it with Scikit-Learn's implementation

PCA with Eigenvalue Decomposition

This article provides a step-by-step guide to performing Principal Component Analysis (PCA) using Eigenvalue Decomposition (EVD), explaining the theoretical foundation, practical implementation, and visualization of principal components in a bivariate dataset

PCA with Single Value Decomposition

This article explains how to perform Principal Component Analysis (PCA) using Singular Value Decomposition (SVD), demonstrating its implementation, variance preservation, and practical applications with detailed examples and visualizations

Linear Regression

This article explains the mathematical foundations, practical implementation, and evaluation of linear regression, including confidence intervals for coefficients and a comparison between manual and Scikit-Learn implementations

Character Analysis

This article analyzes character frequencies and transitions in text using histograms and heatmaps, implementing Python code to visualize and interpret patterns in character dependencies and transitions

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