| Supervised | Fully | Prediction, Interpolation, Identification | Regression models SVMs, Decision Trees/ Random Forest, Neural Networks,SVM, |
| Unsupervised | No-labels | Data comparisons, Visualization and dimensionality reduction, Pattern discovery, Anomaly detection | K-means , Db-scan, Hierarchical Cluster Analysis, PCA, LLE, t-SNE |
| Semi-supervised | Partially-labeled | Generate better results without the cost of data-labeling. | Deep Belief Network, Restricted Boltzmann machines, Distant Supervision |
| Self-supervised | Self-labeled | Embedding Noise reduction, Operations/Planning | Autoregression, Transformers |
| Reinforcement learning | Partially labeled | Robotics | Deep-Q learning |