Luther // w2d3

Winter 2015

Planned schedule and activities

9:00 am: Good morning! Coffee! All of the things! Waiting for laptops.

9:30 am: Diving into Linear Regression with scikit-learn and statsmodels

9:50 am: Work time for the rest of the day. Bored? Here are some things to do:

Lecture Notes

w2d3_Linear_Regression_with_Movies.ipynb (200.8 KB)

Linear Regression Challenges

Challenge 1

We are fitting and checking the predictions on the exact same dataset! Divide your data into two sets: a training and a test set (roughly 75% training, 25% test). Fit a model on the training set, check the predictions (by plotting predicted values versus actual values) in the test set.

Challenge 2

Build a model that also uses average director gross as a feature (one of the predictor variables). Fit and evaluate. Would you use this model to predict gross revenues of upcoming movies?