This project demonstrates the K-Means clustering algorithm using synthetically generated data. It explores the application of K-Means on random datasets with multiple centers, visualizing cluster ...

While digital literacy has become an aspirational cornerstone of modern education, the exponential growth of data-driven decision-making across industries reveals critical gaps that demand a stronger ...

Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...

Introduction: The rising concerns about food security and the increasing demands for meat-based diet in China have highlighted the imbalance between the supply and demand of its feed grains. Scholars ...

Scoring 50 points in an NBA game is rare — but some of the players who’ve done it are even rarer. In this video, I go through the most unexpected and random players to ever drop 50+, and how they ...

Building reliable code, optimizing complex systems, and keeping things running smoothly. Always learning, always shipping. Big fan of clean design, clear logic, and a good challenge.

The dataset consists of transactional data from a UK-based online retail store. It includes all transactions between 01/12/2010 and 09/12/2011. The data contains essential attributes such as: ...