3. Predict House Prices

In this lab, you’re going to write an app in C# that trains a regression machine learning model to predict house prices in California.

We will revisit the California Housing app you developed earlier, and build upon its feature engineering foundation. We’ll extend the ML.NET pipeline and add new steps to train a regression model on the housing data and generate price predictions. You will also calculate the RMSE, MSE and MAE metrics to evaluate your results.

There are many factors that influence the quality of your predictions, including how you process the dataset, which regression algorithm you pick, and how you configure the training hyperparameters. How close can you make your predictions to the actual house prices?

When you have a nice result that you feel proud of, feel free to upload it to the Hall Of Fame!