● Recommendation 1 advertises purchases of other people who buy the same product as the person of interest. It is aimed for a particular customer.
● Recommendation 2 is based on "Frequently Bought Together" idea that recommends items that are usually purchased in the same order. It is aimed for a particular product.
● "orderdata.csv" is the input data where columns denote Order ID, UserId, SKU (item number).
● "Recommendation_1.py" contains the first type of algorithm.
● "Recommendation_1.csv" contains the result of the first type of algorithm. Each row consists of a user id followed by recommendations to that user id.
● "Recommendation_2.py" contains the second type of algorithm.
● "Recommendation_2.csv" contains the result of the second type of algorithm. Each row consists of a reference item followed by recommendations based on that reference item.