We are dedicated to providing access and opportunities for persons with disabilities in their work lives, fostering a sense of community and belonging.
- Compassion: We care deeply about the well-being of every individual.
- Strength: Inspired by the resilience of our community.
- Nurturing: Creating a supportive environment for growth and success.
- Exploration: Encouraging innovation and new possibilities.
- Perspective: Embrace mistakes with humor to grow and learn from them.
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- Fairness: Ensure models do not discriminate against any group.
- Transparency: Provide clear explanations of model decisions.
- Privacy: Protect user data and ensure confidentiality.
- Accountability: Maintain responsibility for AI outcomes.
- Perspective: Embrace mistakes with humor to grow and learn from them.
- Data Handling: Tools for data preprocessing and bias detection.
- Model Training: Methods for training models with ethical considerations.
- Evaluation: Metrics and tools for evaluating model fairness and performance.
- Deployment: Guidelines and tools for deploying models ethically.
pip install ethical-ai-frameworkfrom ethical_ai_framework import DataHandler, ModelTrainer, Evaluator, Deployer
# Data Handling
data_handler = DataHandler()
data = data_handler.load_data('data.csv')
clean_data = data_handler.preprocess(data)
# Model Training
trainer = ModelTrainer()
model = trainer.train(clean_data)
# Evaluation
evaluator = Evaluator()
fairness_metrics = evaluator.evaluate_fairness(model, clean_data)
# Deployment
deployer = Deployer()
deployer.deploy(model)We welcome contributions! Please see our contributing guidelines for more details.
This project is licensed under the MIT License - see the LICENSE file for details.