Welcome to the Machine Learning Tutorials section! Whether you're a beginner or looking to deepen your expertise, here are curated resources to help you explore the world of ML.

🧠 Core Concepts

  • Supervised Learning: Learn how algorithms learn from labeled data (e.g., classification, regression).
  • Unsupervised Learning: Discover techniques for finding patterns in unlabeled data (e.g., clustering, dimensionality reduction).
  • Reinforcement Learning: Understand how agents learn to make decisions through rewards and penalties.
  • Deep Learning: Dive into neural networks and their applications in complex tasks like image recognition.

📘 Learning Resources

💡 Practice Tips

  1. Start with simple projects to build intuition.
  2. Use tools like /en/resource/tools/ml-frameworks for experimentation.
  3. Join communities to discuss challenges and share knowledge.
Neural_Network
Data_Preprocessing
Model_Training