Types of Machine Learning Algorithms

Intermediate

📚 Classification of Machine Learning Algorithms

Machine learning algorithms are classified based on the problem type and learning paradigm. The main categories include:

🎓 Supervised Learning

Uses labeled data to predict outcomes.
Examples:

  • 📈 Linear Regression – for continuous outcomes
  • 🔢 Logistic Regression – for binary classification
  • 🌳 Decision Trees
  • ➗ Support Vector Machines (SVM)

🕵️‍♀️ Unsupervised Learning

Finds hidden patterns in unlabeled data.
Examples:

  • 📊 Clustering algorithms:
    • 📍 K-Means
    • 🧬 Hierarchical Clustering
  • 🔻 Dimensionality Reduction:
    • 📉 Principal Component Analysis (PCA)

🏆 Reinforcement Learning

The model learns to make decisions by receiving rewards or penalties.
Applications:

  • 🎮 Game playing (e.g., AlphaGo)
  • 🤖 Robotics
  • 🔄 Adaptive systems

✅ Understanding the strengths and limitations of each type guides the selection of the appropriate algorithm for specific tasks.