The versatility of BigML allows you to build supervised learning models without much complexity. In this course, you'll practice constructing a selection of supervised learning models using BigML.
You'll start by building an ensemble of decision trees to perform binary classification. Next, you'll build a linear regression model to predict the values of homes in a particular region. You'll then train and evaluate a logistic regression model to illustrate how it can be used to solve similar problems to those solved using ensemble methods.
Another BigML capability you'll explore is building a time series plot to make various forecasts. In each demonstration, you'll delve into some optional configurations for the model being trained. Lastly, you'll use the OptiML feature to find the optimal model for your data.
Learning Objectives
{"discover the key concepts covered in this course"}