1. Supervised Learning Algorithms:
Examples: Linear Regression, Logistic Regression, Decision Trees, Support Vector Machines, Naive Bayes, K-Nearest Neighbors
2. Unsupervised Learning Algorithms:
Examples: K-Means Clustering, Hierarchical Clustering, Principal Component Analysis
3. Reinforcement Learning Algorithms:
Examples: Q-Learning, Deep Q-Learning, SARSA, Monte Carlo Methods
4. Semi-Supervised Learning Algorithms:
Examples: Self-Training, Co-Training, Transductive Support Vector Machines