Machine learning is a subset of artificial intelligence that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention. Here's a concise overview of its core concepts:

Key Concepts

  • Supervised Learning 📚
    Uses labeled data to train models. Example: Predicting house prices based on features.

    Supervised Learning

  • Unsupervised Learning 🧩
    Analyzes unlabeled data to discover hidden structures. Example: Customer segmentation.

    Unsupervised Learning

  • Reinforcement Learning 🎮
    Learns through reward/penalty mechanisms. Example: Training AI in games like chess.

    Reinforcement Learning

Learning Process

  1. Data Collection 📁
  2. Model Training 🔄
  3. Evaluation & Optimization 📈
  4. Deployment 🚀

For deeper insights, explore our introduction to machine learning. 🌐