It is recommended that you start with a dataset of at least five years of data and more than 100 different products. The bigger the better, but if you do not have data available that size, then any will do for this exercise.

Prepare your data then run the linear regression and decision tree algorithm ML code in Jupyter Notebook.

You will need to adjust the parameters accordingly, including defining how the data will be extracted from the csv file and format using dates as columns ('Year' + '-' + 'Month') and the products ('Make' or 'SKU' or "Product' etc.) as lines or rows.

Compare the results of the Train RMSE and Test RMSE obtained for each.

Using the 'text' option on Canvas,

Post an overview of your topic and the dataset chosen.

Share your results and the conclusions drawn about method is a better predictor of the outcome.

What issues did you run into, and how were you able to resolve them?