- š Hi, Iām @SagerKudrick
- š« reach me at [email protected]
Witness an innovative application of Differential Privacy in conjunction with state-of-the-art Machine Learning models here.
- Demonstrates the fusion of Differential Privacy with modern Machine Learning, focusing on the MNIST dataset for digit classification.
- Achieves high accuracy in predictions while safeguarding data privacy.
- Shows how differential privacy enhances model security without compromising performance.
Explore my Flask/React Game Catalog project here.
- Developed a Flask API with endpoints for seamless filtering and CRUD operations on an SQL database.
- Engineered a React frontend in JavaScript to showcase data from the Flask API, enabling users to execute CRUD operations instantly.
- Deployed to a cloud Linux server for 24/7 operation using PuTTy, OpenSSH, and FileZilla.