This project applies the Apriori algorithm on the Instacart dataset to uncover frequent item associations. Using the arules package in R, we analyze transaction data to identify product combinations often purchased together. The findings provide insights for personalized recommendations and targeted marketing. Visualizations of the rules highlight strong associations, helping businesses optimize product placements and promotions.

This project explores dimensionality reduction techniques (PCA and t-SNE) applied to FIFA 23 players' data to identify patterns and visualize high-dimensional data in a reduced form

Provide a brief description of what the document is about. For example: "This analysis performs customer segmentation on a mall dataset using K-Means clustering, Hierarchical clustering, and DBSCAN. The goal is to explore how different clustering algorithms group similar customers based on age, annual income, and spending score."