Examples

This section provides detailed examples for using SecureML’s features. Each example demonstrates practical implementations to help you get started with privacy-preserving machine learning tasks.

Example Categories:

• Anonymization Examples
  • k-Anonymity
  • Pseudonymization
  • Data Masking
  • Generalization
• Compliance Checking Examples
  • Basic Compliance Check
  • Using ComplianceAuditor
  • Generating PDF Reports
  • Supported Regulations
• Audit Trail Examples
  • Basic Audit Trail Creation
  • Using the Audit Function Decorator
  • Retrieving and Analyzing Audit Logs
  • Generating Reports from Audit Logs
  • Integration with Other Features
• Differential Privacy Examples
  • PyTorch Model with Differential Privacy
  • TensorFlow Model with Differential Privacy
  • Privacy-Utility Tradeoff
  • Federated Learning with Differential Privacy
  • Advanced Options and Best Practices
• Federated Learning Examples
  • Basic Federated Learning with PyTorch
  • Federated Learning with TensorFlow
  • Privacy-Preserving Federated Learning
  • Comparing Weight Update Strategies
  • Client-Server Deployment
  • Best Practices
• Synthetic Data Generation Examples
  • Basic Synthetic Data Generation
  • Statistical Method
  • Automatic Sensitive Column Detection
  • Schema-Based Generation
  • Advanced Synthetic Methods
  • Comparing Methods
  • Evaluating Synthetic Data Quality
  • Complete Example
  • Best Practices
• Report Generation Examples
  • Basic Compliance Reports
  • Reports From Compliance Checks
  • Audit Reports
  • Customizing Reports
  • Combined Reports
  • Scheduled Reports
  • Complete Example
  • Best Practices
• CLI Examples
  • Basic Setup
  • Anonymization Examples
  • Compliance Checking Examples
  • Synthetic Data Generation Examples
  • Regulation Presets Examples
  • Isolated Environment Examples
  • Key Management Examples
  • End-to-End Example Workflow
  • Processing Multiple Files
  • Performance Considerations