Project AirBnB

This project is a six-hour Kaggle competition, demonstrating my ability to use regression and random forest classifier models on an AirBnB dataset for a time-constrained hackathon.

I setup (cleaned and prepped the data), fit, scored, and presented two machine learning models during this challenge. I improved the model accuracy from 0.58 to 0.62 (so not very much), but still an accomplishment given the time-constraint and my newbie status.

I realize this project looks pretty basic, but included it as a reminder of the importance to maintain a learning mindset, and how far I’ve progressed on my data science journey.