Predicting behavior based on existing data to produce a preventive rather than reactive money saving strategy.

What it does

Tracks spending through CapitalOne's Nessie API and predicts behavior using a decision tree produced from the data collected. Alerts the user when an item not aligning with their behavior is added to their cart on shopping websites.

How we built it

We used python and the requests package to retrieve data using the Nessie API and the pandas library to analyze the data. We used javascript, html, and css to build the Google Chrome Extension.

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