Tutorial 3: Regression and Project Consultation

This week we’ll recap Linear Regression and look at various ways to implement regression models for your projects. We’ll cover penalised regression models (LASSO and Ridge) and see how we can implement regression for data in both Pandas and PySpark.

Project 1 Reminder

Important

>50% time elapsed ⏳⌛*

Tutorial Outline

In the session today we will:

1. Cover the final part of last week’s content.

2. Fit linear models on a sample of our taxi data.

3. Perform model selection.

4. Discuss/recap LASSO and Ridge regression (penalised regression).

5. Fit penalised regression models using glmnet.

6. Fit regression models using pyspark.ml.

7. Spend the rest of the tutorial consulting about project 1.

8. (Optional) Cover some optional additional revision content if we get through everyone’s questions.