Used the nearest neighbour classifier and ML with scikit-learn to train a model to determine a user’s purchasing intent based on data from previous visits. Huge credits go to Harvard's Online AI course, since the project was assigned from them.
Trains a model based on half the inputed data, then tries to predict the purchasing intent (whether the viewer is going to buy something or not) for the other half of the data and then returns the amount of predictions gotten correct/incorrect.
dependancies: pip3 install scikit-learn
$ python shopping.py shopping.csv
Correct: 4088
Incorrect: 844
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