Supervised Learning

• Statistical regression.
• Statistical classification.
• Statistical clustering (Cluster analysis).
• Dimensionality reduction.

Semi-Supervised Learning (SSL)

• Self-training.
• Co-training.
• Generative Adversarial Networks (GANs) for SSL.
• Graph-based SSL.

Reinforcement Learning

• Q-Learning.
• State-Action-Reward-State-Action (SARSA).
• Deep Q-Networks (DQN).
• Policy Gradient Methods.
• Actor-Critic Methods.
• Deep Deterministic Policy Gradient (DDPG).
• Proximal Policy Optimization (PPO).
• Trust Region Policy Optimization (TRPO).

Ensemble Learning

• Bootstrap Aggregating (aka Bagging).
• Random Forest of Decision Trees.
• Boosting weak learning methods into strong learners.
• Gradient Boosting.
• Adaptive Boosting (AdaBoost).
• Stacking.
• Voting Classifier.
• Blending.

Deep Learning

• Convolutional Neural Networks (CNN).
• Recurrent Neural Networks (RNN).
• Long Short-Term Memory Networks (LSTM).
• Gated Recurrent Unit (GRU).
• Auto-encoders.
• Generative Adversarial Networks (GANs).
• Transformer Networks.
• Bidirectional Encoder Representations from Transformers (BERT).
• Generative Pre-trained Transformer (GPT).

Probabilistic Reasoned Learning

• Bayesian Networks.
• Hidden Markov Models (HMM).
• Markov Chain Monte Carlo (MCMC).
• Gaussian Processes.

Instance-Based Learning

• K-Nearest Neighbors (KNN).
• Locally Weighted Learning.
• Case-Based Reasoning.

Evolutionary (Darwinian) Learning

• Genetic Algorithms (GA).
• Genetic Programming (GP).
• Evolutionary Strategies (ES).
• Differential Evolution (DE).

Hybrid Learning

• Neural Evolution (Neural nets and GA).
• Neuro-Fuzzy Systems (Neural nets and fuzzy logic).