Autonomous ML
Optimization Framework

Enterprise-grade hyperparameter optimization and explainability.
No cloud required. No GPU farm needed.

$ pip install corter

$ python

> from corter import Corter

> core = Corter.from_yaml("config.yaml")

> result = core.run("data.csv")

# Lightning-fast HPO with parallel execution

# Advanced XAI with SHAP integration

# Beautiful web dashboard included

Built for ML Engineers

Multiple strategies including random search, differential evolution, and local optimization. Parallel execution with intelligent early stopping.

SHAP integration, permutation importance, mutual information analysis, and drift detection. Understand your models deeply.

Beautiful browser-based interface with real-time progress tracking, interactive charts, and live insights. No terminal required.

Robust error handling, backward compatibility, comprehensive documentation, and Railway deployment support out of the box.

# Create config.yaml

task: classification

target_column: target

hpo:

strategy: random

n_trials: 24

parallel_trials: 4

enable_early_stop: true

# Run optimization

$ python corter_web.py config.yaml data.csv

# View results at http://localhost:5000