seattle-911-md-gist
In this post, we'll explore an alternative universe, in which the city of Seattle receives 911 calls for only four reasons: an accident involving beavers, a seal attack, a Marshawn Lynch sighting, or a hot latte spills in someone's lap.
We're given a data set consisting of the 911 call logs. Our task is to learn from this data to predict the reason for any 911 call. Working in Python, we'll learn how to examine the data via exploratory data analysis (EDA). Using the scikit-learn library, we'll build a Random Forest model and train it to predict the type of 911 call based on patterns in the data. We'll test our model by making predictions and evaluating its performance.
Along the way, you'll encounter and absorb a numberr of key concepts that are at the heart of the data science process. Ready? Come along, then. As Chris Cuomo would say: "Let's get after it!"