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The goal of this project is to extract valuable insights from transaction data, understand customer purchasing behaviour and use it for business optimization.
These are the libraries I used for this project:
- Data Exploration & Preprocessing :
pandas - Data Visualization :
matplotlibseaborn - MBA:
TransactionEncoderassociation_rules, apriori
With the above libraries, we will test the idea that one can predict purchasing patterns within items, which is what makes MBA popular in the field of retail and commerce. This form of analysis helps many forms of businesses understand behavioral patterns and purchase patterns. The idea is to find the link between purchased items. For example, if someone purchases Item1, how likely are they to then also purchase Item2? Check out the python file for the code and results.
Image Source: Photo Source
