Tutorials
Classification
Learn how to prepare the data for modeling, create a classification model, tune hyperparameters of a model, analyze the performance, and consume the model for predictions.
Regression
Learn how to prepare the data for modeling, create a regression model, tune hyperparameters of a model, evaluate model errors, and consume the model for predictions.
Clustering
Learn how to prepare the data for modeling, create a K-Means clustering model, assign the labels, analyze results, and consume a trained model for predictions on unseen data.
Anomaly Detection
Learn how to prepare the data for modeling, create an unsupervised anomaly detector, evaluate the results of the trained model, and consume the model for predictions on unseen data.