Quick start: sample model

Train ML or forecasting in ~10 minutes — no spreadsheet, no Data lake.

Before you start

• Free account → create one
• Signed in at heimdallapp.org

ML with Housing or Iris

1. Machine Learning → New model
2. Sample datasets → pick Housing or Iris
3. Choose target column (MEDV or species column)
4. Name the model → Train
5. Training queue → open the model when done → copy API keys

Housing vs Iris

Housing = regression (predict a number). Iris = classification (predict a category).

Forecast with AirPassengers

1. Forecast → new build
2. Sample dataset → AirPassengers
3. Interval → Monthly → review analysis
4. Name it → start training

Next steps

• Deploy ML or deploy forecast
• Ready for real data? → Quick start: your data

FAQ

No file upload in the wizard?
Production data goes through the Data lake as gold. Samples skip that so you can explore.

Samples are for learning

Do not use built-in samples in production. Publish your own gold for real projects.