Top 5 Types of Machine Learning

Supervised Learning
Trains models on labeled data to predict outcomes. Commonly used for classification and regression tasks.
Examples: Spam detection, image recognition.
Unsupervised Learning
Discovers patterns in unlabeled data without predefined categories.
Examples: Customer segmentation, anomaly detection.
Semi-Supervised Learning
Combines a small amount of labeled data with a large amount of unlabeled data to improve learning accuracy.
Examples: Text classification, image classification.
Reinforcement Learning
Uses trial and error, allowing agents to learn optimal actions through rewards and penalties.
Examples: Game playing, robotics.
Deep Learning
A subset of machine learning using neural networks with many layers to analyze complex patterns.
Examples: Speech recognition, natural language processing.