Association Rule Mining with Apriori Algorithm

Developed a data mining project to discover hidden patterns and relationships between items in transactional datasets using the Apriori algorithm. Implemented data preprocessing and transformation to convert transactional data into a suitable format for association rule mining. Generated frequent itemsets and extracted association rules based on metrics such as support, confidence, and lift. The project demonstrates how businesses can identify product relationships and improve strategies such as market basket analysis, recommendation systems, and cross-selling opportunities.