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Techniques used for data cleaning, finding patterns in structured, text, and web data; with application to areas such as customer relationship management, fraud detection & homeland security.
MBA involves analyzing customer transaction data to identify which products are purchased together in the same basket or transaction. The analysis is typically done by looking at the frequency of co-occurrence of items in the transaction data, and then applying statistical techniques to identify which items are most frequently purchased together.
This repository provides a practical learning ground for data analysis with code and visualizations. Explore techniques like Apriori algorithm, EDA, K-Means clustering, and more!