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Real Incognito - AI Data Anonymizer
2024
PythonGANMachine LearningPytorch
A GAN-based data anonymization system that preserves data utility while removing sensitive information. Won 2nd place in AI domain at hackathon.
Developed an innovative solution using Generative Adversarial Networks (GANs) to anonymize sensitive data while maintaining its statistical properties and utility. The system uses a custom generator model to create synthetic data that preserves the performance characteristics of the original dataset while removing all personally identifiable information.
Key Features
- GAN-based data generation for privacy preservation
- Custom loss functions for utility preservation
- Real-time data anonymization pipeline
- Evaluation metrics for data utility assessment
Technology Stack
AI/ML
PyTorchGANCustom Neural Networks
Tools
DockerGitJupyter Notebooks
Challenges
- Balancing privacy and data utility
- Optimizing GAN training for stable results
- Handling different types of sensitive data
Key Learnings
- Advanced GAN architectures and training techniques
- Privacy-preserving machine learning
- Data utility metrics and evaluation
Screenshots
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Achievements
- 2nd Place in AI Domain at Hackathon