Summary

In this chapter, we discussed regression models in detail and saw how to create single-input and multi-input regression models. We learned how easy it is to predict a numeric value. We also learned how to validate regression models, take actions to improve our model’s accuracy, and do prediction queries with our regression models. We walked through options for using XGBoost, Linear Learner and auto options to train your model.

We also saw how we can check and validate the MSE score from the SHOW MODEL output using SQL commands in Redshift.

In the next chapter, we will show you how to create unsupervised models using the K-means algorithm.