I used reinforcement learning to train a self-driving car how to drive in an idealized grid-like city, where may be present other vehicles and traffic light, but no pedestrians.

I mostly used the Python libraries Pandas and Sklearn to wrangle and built the model and Seaborn to visualize the data. This project is connected to the Machine Learning Engineer Nanodegree program, from Udacity.