tutorials.rst

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.

• Binary Classification Tutorial - Level Beginner (CLF101)
• Binary Classification Tutorial - Level Intermediate (CLF102)
• Multiclass Classification Tutorial - Level Beginner (MCLF101)

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.

• Regression Tutorial - Level Beginner (REG101)
• Regression Tutorial - Level Intermediate (REG102)

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.

• Clustering Tutorial - Level Beginner (CLU101)

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.

• Anomaly Detection Tutorial - Level Beginner (ANO101)

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.

• Natural Language Processing Tutorial - Level Beginner (NLP101)
• Natural Language Processing Tutorial - Level Intermediate (NLP102)

Association Rule Mining

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

• Association Rule Mining Tutorial - Level Beginner (ARUL01)