1. Linear Regression: Predict continuous values.
2. Logistic Regression: Classify data into categories.
3. Decision Trees: Make decisions based on rules.
4. Naive Bayes: Classify text and data.
5. K-Nearest Neighbors: Classify based on similarity.
6. Support Vector Machines: Find optimal decision boundary.
7. Random Forest: Combine multiple decision trees.
8. K-Means Clustering: Group similar data points.
9. Hierarchical Clustering: Create hierarchical clusters.
10. Principal Component Analysis: Reduce data dimensions.