Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computers to perform specific tasks without explicit instructions. Instead of being programmed to complete a task, ML systems learn from data and improve their performance over time.
There are different types of machine learning, here are the three most common machine learning method
1.Supervised Learning:
- Involves training a model on labeled data, where the outcome is known. The model learns to map inputs to outputs. Examples include classification (e.g., email spam detection) and regression (e.g., predicting house prices).
2.Unsupervised Learning:
- The model learns from unlabeled data, identifying patterns and relationships without predefined outcomes. Common techniques include clustering (e.g., customer segmentation) and dimensionality reduction (e.g., PCA).
3.Reinforcement Learning:
- This type involves training models through a system of rewards and penalties. The model learns to make decisions by interacting with an environment, commonly used in robotics and game-playing AI.