Wanted to try working with an API and using OAUTH with ML.

What it does

It is supposed to pull logged in customer data from a quickbooks account and determine relationships between periods of high spending and the sort of person prone to that kind of spending.

How we built it

The backend was written in node.js and express.js. The quickbooks npm repository was very helpful. Machine learning was supposed to play a part, but I wasn't capable of integrating it sufficiently.

Challenges we ran into

As this was my first time using javascript on the backend, I ran into issues compiling the project because I wasn't handling asynchronous operations properly. Because of that I wasn't able to correctly integrate ML.

Accomplishments that we're proud of

Successfully using OAuth 2 and basic MVC architecture.

What we learned

A lot about async javscript

What's next for Intuit API - Customer Data Trends

Hopefully getting async to work and subsequently processing the data with some machine learning models and displaying it using some visual framework like react.js.

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