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HeerakKashyap added 12 commits June 22, 2025 00:40
- Implement Model-Agnostic Meta-Learning (MAML) classifier
- Add Prototypical Networks for few-shot learning
- Create domain adaptation utilities with fine-tuning and MAML methods
- Add transfer learning capabilities with feature extraction and fine-tuning
- Include utility functions for creating and evaluating few-shot tasks
- Add CLI commands: few-shot-learn, domain-adapt, transfer-learn
- Update models_dict to include few-shot learning algorithms
- Add few_shot_learning as supported model type
- Create comprehensive documentation and examples
- Add complete test suite for all few-shot learning components
- Update README with new features and model table

This addresses GitHub issue nidhaloff#237 'Add Support for Few-Shot Learning'
…em (Issue nidhaloff#233)

- Implement MLflow-like experiment tracking with ExperimentTracker class
- Add model versioning with lineage tracking and metadata management
- Create experiment visualization and analysis capabilities
- Include SQLite database for experiment and model metadata storage
- Add support for metric tracking, parameter logging, and model logging
- Implement experiment comparison and visualization tools
- Add model lineage visualization and deployment tracking
- Include interactive Plotly dashboards for experiment analysis
- Support for experiment export and model version management
- Add comprehensive documentation and examples

This addresses GitHub issue nidhaloff#233 'Create Model Versioning and Experiment Tracking'
- Add SyntheticDataGenerator class for creating test datasets
- Support for classification and regression data generation
- Quick function for generating sample datasets
- Addresses GitHub issue nidhaloff#285 - Add Support for Synthetic Data Generation
- Add ModelInterpreter class with feature importance and partial dependence
- Implement prediction explanation and comprehensive model reports
- Include quick functions for model interpretation and feature importance
- Add demo script showcasing interpretability capabilities
- Update package imports to include model interpretability modules
- Addresses GitHub issue nidhaloff#299 - Add Model Interpretability Tools
…f#342)

- Implemented ModelFairnessDetector class with demographic parity, equalized odds, and disparate impact detection
- Added BiasMitigation class with sample reweighting and fairness constraints
- Created example YAML configuration file
- Added demo script for demonstration
- Added test file structure
- Addresses GitHub Issue nidhaloff#342
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