🧺 Project Summary: Market Basket Analysis of Big Basket
This project performs Market Basket Analysis on Big Basket’s product data to uncover relationships between items frequently purchased together. Using association rule mining (Apriori algorithm), the notebook identifies frequent itemsets and strong association rules to help understand consumer buying patterns.
The insights can be applied for:
Product bundling and cross-selling strategies
Personalized recommendations
Inventory planning and marketing optimization
🔹 Key Techniques & Tools
Python, Pandas, NumPy, Matplotlib, Seaborn
MLxtend’s Apriori & AssociationRules for pattern mining
Data cleaning, exploratory analysis, and visualization
🔹 Outcome
The analysis reveals which products customers tend to buy together, enabling data-driven decisions in e-commerce marketing and sales.