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Heimdall ML

Heimdall ML is the no-code machine learning product on Heimdall by RejiCo — build and deploy classification and regression models from gold datasets or explore with Housing/Iris samples.

Before you start
PathRequirement
Your dataGold published for ML, status ready, 100+ rows
SamplesNothing — use wizard Sample datasets

Open ML in the app

Sidebar → Data IntelligenceMachine Learning (/ml)

  • New model — opens training wizard
  • Training queue — in-flight jobs
  • Model list — completed models with deploy status (green dot = API key active)

ML vs Forecast vs Loop

MLForecastLoop
PredictsCategory or number from featuresFuture values over timeCategory/number that improves live
Gold required?Yes (or samples)Yes (or AirPassengers sample)No — separate wizard
SidebarMachine LearningForecastLoop

Full table: What is Heimdall?

What you can build

Classification — churn, fraud, quality grades, species
Regression — pricing, demand scores, risk values

Typical path

  1. Lake → gold (or samples)
  2. Build a model
  3. Deploy
  4. Monitor

Common mistakes

  • Uploading CSV in the wizard — disabled except samples; use Lake → gold
  • Empty gold picker — publish with Machine learning use case, status ready

FAQ

Do I need Lake for every ML model?
No — Housing and Iris samples skip Lake. Production data requires Gold publish.

What's the difference between ML and Forecast?
ML predicts a category or number from feature columns. Forecast predicts future values over a time axis. See product chooser.

Can I upload CSV in the ML wizard?
Only for built-in samples. Your spreadsheets go through Lake → Gold first.

Next steps