Using BigML: Building Supervised Learning Models

“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.”