Community Edition Notebooks
A collection of Jupyter notebooks that demonstrate the extensive features and capabilities of the getML Community Edition. These notebooks are designed to cover a wide range of data types, prediction tasks, difficulty levels, and application domains, providing an excellent foundation for your own projects.
Note
Community Edition notebooks can be run locally or on Google Colab without restrictions, while some features in the Enterprise Edition notebooks require a license for full functionality.
Overview
| Notebook | Prediction Type | Population Size | Data Type | Target | Domain | Difficulty | Comments |
|---|---|---|---|---|---|---|---|
| adventure_works.ipynb | Classification | 19,704 | Relational | Churn | Customer loyalty | Hard | Good reference for a complex data model |
| formula1.ipynb | Classification | 31,578 | Relational | Win | Sports | Medium | |
| interstate94.ipynb | Regression | 24,096 | Time Series | Traffic | Transportation | Easy | Good notebook to get started on time series |
| loans.ipynb | Classification | 682 | Relational | Default | Finance | Easy | Good notebook to get started on relational data |
| robot.ipynb | Regression | 15,001 | Time Series | Force | Robotics | Medium | |
| seznam.ipynb | Regression | 1,462,078 | Relational | Volume | E-commerce | Medium |
Source
These notebooks are published on the getml-community repository.