end-to-end-bluebook-bulldozer-price-regression

Prices of Bulldozers

🚜 Predicting the Sale Price of Bulldozers using Machine Learning

In this notebook, we're going to go through an example machine learning project with the goal of predicting the sale price of bulldozers.

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.

The techniques used in here have been inspired and adapted from the fast.ai machine learning course.

What we'll end up with

Since we already have a dataset, we'll approach the problem with the following machine learning modelling framework.

6 Step Machine Learning Modelling Framework (read more)

To work through these topics, we'll use pandas, Matplotlib and NumPy for data anaylsis, as well as, Scikit-Learn for machine learning and modelling tasks.

Tools which can be used for each step of the machine learning modelling process.

We'll work through each step and by the end of the notebook, we'll have a trained machine learning model which predicts the sale price of a bulldozer given different characteristics about it.