(The is a follow-along tutorial project done in the course "Complete AI & Machine Learning, Data Science Bootcamp" by Andrei N. & Daniel B.")
In this Jupyter notebook, we're going to go through an example ML project with the goal of predicting the sale price of bulldozers using "Structured Data".
Since we're trying to predict a number, this kind of problem is known as a "Regression" problem.
The data and evaluation metric we'll be using (root mean square log error or RMSLE) is from the Kaggle Bluebook for Bulldozers competition.(https://www.kaggle.com/c/bluebook-for-bulldozers/overview)
The techniques used in here have been inspired and adapted from the fast.ai machine learning course.(https://course18.fast.ai/ml)