SmartEco is an open-source repository for building and evaluating CPU-first, interpretable machine learning systems.
The project focuses on practical system design for machine learning — prioritizing latency, predictability, and transparency over benchmark-only accuracy.
A production-oriented nearest-neighbor engine designed for:
- Fast CPU inference
- Predictable latency
- Transparent decision logic
SmartKNN extends classical KNN with learned feature weighting, adaptive distance computation, and backend strategies optimized for real-world constraints.
A benchmarking and inspection toolkit for:
- Comparing ML and DL models under identical conditions
- Measuring accuracy, latency, and tail behavior
- Selecting model families before production work
SmartML is not AutoML and not a production pipeline.
It exists to provide trustworthy baseline numbers and transparent evaluation.