Hyperparameter Tuning Kit
Optuna/Ray Tune configs, search space definitions, pruning strategies, and distributed tuning setups.
📊 Model Performance Dashboard
Evaluate model metrics interactively. Adjust thresholds and see how they affect precision, recall, and F1 scores.
⚡ Hyperparameter Tuner
Adjust learning rate, batch size, and epochs to see predicted training outcomes.
Included with Hyperparameter Tuning Kit
The complete Hyperparameter Tuning Kit package includes:
- SearchSpace + typed params + RandomTrial (stdlib)
- Median/percentile/threshold pruners + early stopping
- Scorers, K-fold CV, Objective (multi-objective)
- Best/top-k, importance, Pareto, export (stdlib)
- StudyConfig + runstudy (lazy optuna)
- TuneConfig + runtune, ASHA/PBT (lazy ray)
Get the Full Hyperparameter Tuning Kit
This demo shows limited functionality. The full version includes all features, source code, documentation, and lifetime updates.
Buy Full Version — $29.00