🚀 30 Days of Federated Learning Code (#30DaysOfFLCode)

Welcome to my repository! 🎯

This is my journey into the world of Federated Learning (FL), where I explore its concepts, techniques, and real-world applications. Over the next 30 days, I will dedicate time daily to learning and documenting my progress here. 🌐🔒

🎯 Challenge Goals

1️⃣ Daily Learning: Spend at least 1 hour each day studying Federated Learning.
2️⃣ Daily Updates: Share reflections, insights, and takeaways from each session.
3️⃣ Collaboration: Connect with others passionate about FL and machine learning to share knowledge and ideas.

📚 What to Expect

This repository will feature:

• Daily Updates: Logs and insights from each day’s learning.
• Mini Projects (if applicable): Hands-on implementation of FL concepts.

🌟 Why Federated Learning?

Federated Learning is a cutting-edge approach to training machine learning models while ensuring data privacy. It enables collaboration across decentralized datasets without transferring raw data, opening doors to exciting possibilities in AI and privacy.

📝 Daily Progress

• Day 1: Introduction to Federated Learning.

(Progress will be updated daily!)

💬 Let’s Connect!

If you’re also exploring Federated Learning or have resources to share, feel free to:

• Follow the journey: Stay tuned for updates here or on LinkedIn.

Email - [email protected]