Differentiation Based on Supervised Learning Unsupervised Learning Reinforcement Learning
Features The training set has both predictors and predictions. The training set has only predictors. It can establish state-of-the-art results on any task.
Linear and logistic regression, support vector machine, and Naive Bayes
K-means clustering algorithm and dimensionality reduction algorithms Q-learning, state-action-reward-state-action (SARSA), and Deep Q Network (DQN)
Uses Image recognition, speech recognition, forecasting, etc. Preprocessing data, pre-training supervised learning algorithms, etc. Warehouses, inventory management, delivery management, power system, financial systems, etc.