Machine Learning Projects via ml-pyproj

Welcome to the ml-pyproj repository, a comprehensive collection of Machine Learning enabled processes integrated with DevOps guidelines implemented using Python and UI as Hugo.

💡 Categories

1. ml-pipelines: Projects focused on ML workflows and DevOps integrations.

🚀 Workspace (s)

This repository utilizes two environments: development and production through GitHub-Actions to enssure CI/CD pipelines are in place.

• development.yml
• production.yml

🛠️ Code Quality and Model Tracking

1. This repository uses CodeQL via GitHub-Actions for code scanning to ensure security and quality.

2. The ml-pipelines utilize mlflow for tracking and managing experiments, ensuring reproducibility and efficiency.

3. Projects follow SOLID principles for high code quality:

   • Single Responsibility Principle
   • Open-Closed Principle
   • Liskov Substitution Principle
   • Interface Segregation Principle
   • Dependency Inversion Principle

🤝 Reach Out for Collaboration

📫 Reach out via LinkedIn or Email

Thank you. Cheers!! 🥂

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