TEAM PEAK

Inspiration

We were inspired to do this track because it posed a great challenge that everyone in the group could contribute to. Moreover, it also had a lot of room to learn from other team members as the challenge moved forwards.

What it does

Our analysis goes into depth based on what circumstances would provide a related oil production amount for Chevron. This program essentially filters data that will be important to understanding the process, and creates a model to use to attempt to predict what would happen in different scenarios.

How we built it

We used various data science techniques such as random forests, and then used seaborn/matplotlib for plotting and visualization.

Challenges we ran into

We initially struggled with setting everything up in order to begin working together, but eventually followed through with alternative methods of being able to continue working on the same project.

Accomplishments that we're proud of

We managed to reduce the overall error by a significant amount compared to what we were originally anticipating when working with the model. In addition, we were able to utilize skills outside of data science (such as an art background) to be able to make great visualizations.

What we learned

We learned that it was possible for everyone to be able to participate, and that the talents of each team member paired with cohesive communication can result in an astounding amount of work done in a small amount of time.