📚 Machine Learning Resources

Welcome to the Machine Learning resources page! Here you'll find curated materials to help you dive into the world of ML. 🚀

📋 Key Learning Areas

• Basics
  Start with foundational concepts like supervised/unsupervised learning.

  [Read more about ML fundamentals](/en/resources/machine_learning_fundamentals)

• Tools & Libraries
  Explore popular frameworks:

  • Python ML Libraries
  • TensorFlow Tutorials
  • PyTorch Documentation
  

• Projects & Examples
  Practice with real-world applications:

  • Beginner Project: Iris Classification
  • Intermediate Project: Image Recognition
  • Advanced Project: NLP Models
  

🧠 Recommended Learning Path

1. Understand ML algorithms
2. Learn data preprocessing techniques
3. Explore model evaluation metrics

📈 Visual Guides

[View the ML workflow diagram](/en/resources/ml_workflow)

For hands-on practice, check out our interactive coding environment. 🌐🔧