Conoco Phillips Hack

Inspiration

Oil and Gas is a backbone on the global scale and incorporating new machine learning and technology to the historical field. Conoco Phillips gave us a great idea to visualize our passion for great customer/client service and cutting-edge technology.

What it does

This is a full stack API that gives the user a straightforward approach on our utilization of a kernel regression machine learning model. This type of regression avoids overfitting of the ML model allowing high variance and multiple variables.

How we built it

Tech - (React, Node, JavaScript, HTML, TailwindCSS (and CSS), Python, Flask, Git, GitHub) and teamwork!

Challenges we ran into

Merging, React, debugging (all resolved)

Accomplishments that we're proud of

Won Second place for the Conoco Phillips track!

What we learned

Lots about machine learning and the difficulty of working with strong individuals, as well as many introductions to the frustrations of javascript.

Thanks to the team - M. Khan, M. Farah, M. Chalitsios, K. Zheng

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