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.

Natural Language Processing

Learn how to perform text preprocessing, tune hyperparameters of a topic model and consume the results of a topic model in supervised experiment i.e. Classification or Regression.

Association Rule Mining

Learn how to prepare data for association rule mining. Create an apriori model, examine rules, and analyze results.