In this Post I will go through the workflow of a full machine learning project with the Ames housing dataset, using Linear Regression. This post was initially created with Jupyter Notebook. Unfortunately with WordPress, it is only possible to display a Jupyter Notebook in a small window, like you can see below. Therefore I would recommend you to view it on github, because it is better displayed there.
Table of Contents:
- Part 1: Data Exploration
- Part 2: Missing Data
- Part 3: Out liars
- Part 4: Kurtosis, Skewedness etc.
- Part 5: Deleting Categorical Features
- Part 6: Converting Categorical features
- Part 7: repeat feature-engineering at test_df
- Part 8: Train & Test the Model