Step 1.2 – Types of Machine Learning

1. Supervised Learning

In supervised learning, the model learns from labeled data. You provide both the input and the correct output. The model learns the mapping between them.

Examples: Predicting house prices, spam detection

2. Unsupervised Learning

Unsupervised learning deals with unlabeled data. The model tries to find hidden patterns or groupings without knowing the correct answers.

Examples: Customer segmentation, anomaly detection

3. Reinforcement Learning

Reinforcement learning involves learning through interaction with an environment. The model receives feedback in the form of rewards or penalties and adjusts its strategy accordingly.

Examples: Game-playing AI, robotics

Summary Table