ArcoreTrainR
Beginner-friendly ML platform with guided workflow engine, dataset analyzer, and polyglot algorithm library. Sprint 6 adds production dashboards: experiment tracker, model registry, fairness monitor, and A/B testing for model variants.
Key Features
- Interactive decision tree and dataset analyzer to recommend algorithms/metrics
- Polyglot algorithm library with code examples (Python, R, MATLAB, Julia, Scala)
- Experiment tracker with runs, metrics, tags, and history
- Model registry for versioned deployments
- Fairness monitor for bias detection and reporting
- A/B testing for model variants with significance tracking
Usage Example
# Create an experiment and log a run
curl -H "Authorization: Bearer $TOKEN" -X POST https://trainr.internal/api/experiments -d @experiment.json
curl -H "Authorization: Bearer $TOKEN" -X POST https://trainr.internal/api/experiments/{id}/runs -d @run.json
# Analyze fairness and start an A/B test
curl -H "Authorization: Bearer $TOKEN" -X POST https://trainr.internal/api/fairness -d @fairness.json
curl -H "Authorization: Bearer $TOKEN" -X POST https://trainr.internal/api/ab-tests -d @abtest.jsonTech Stack
Authentication
- •**Header:** `Authorization: Bearer <token>`
- •**Scopes:** Experiments, registry promotions, fairness reports, and A/B test management.
Compliance & Security
Compliance
- ✓Experiment/registry history provides audit trail for model decisions
- ✓Fairness monitor surfaces bias and can gate promotions
- ✓Token-based auth with role-based permissions; production DB on PostgreSQL
Security
- ✓TLS 1.3
- ✓AES-256 encryption
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