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AI Glossary

AI terms. Simplified.

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Model Training & Adaptation

• Active learning
• Actor-critic
• Anomaly detection
• Automated machine learning
• Autoregressive model
• Backpropagation
• Bagging
• Bias-variance tradeoff
• Binary classification
• Boosting
• Catastrophic forgetting
• Categorical feature
• Causal AI
• Causal inference
• Checkpoint
• Class imbalance
• Classification (machine learning)
• Clustering
• Confounding
• Continual learning
• Contrastive learning
• Cross-validation
• Curriculum learning
• Data augmentation
• DBSCANDensity-based spatial clustering of applications with noise
• Decision boundary
• Decision tree
• Deep reinforcement learning
• Dimensionality reduction
• Direct preference optimizationDPO
• Discriminative model
• Distillation
• Domain adaptation
• Dropout
• Early stopping
• Ensemble learning
• Exploration-exploitation tradeoff
• Feature engineering
• Feature importance
• Feature scaling
• Feature selection
• Federated learning
• Few-shot learning
• Fine-tuning
• Gradient
• Gradient boosting
• Gradient descent
• Grid search
• Hierarchical clustering
• Hyperparameter tuning
• K-means
• k-nearest neighbors
• Knowledge distillation
• L1 regularization
• L2 regularization
• Linear regression
• Logistic regression
• Logit
• LoRALow-rank adaptation
• Machine unlearning
• Meta-learning
• Multiclass classification
• Multilabel classification
• Multitask learning
• Naive Bayes
• Numerical feature
• One-hot encoding
• Online learning
• Optimizer
• Policy (reinforcement learning)
• Policy gradient
• Preference data
• Principal component analysis
• Prompt tuning
• Proximal policy optimization
• Pseudo-labeling
• Q-learning
• Random forest
• Random search
• Regression (machine learning)
• Regularization
• Reinforcement learningRL
• Reinforcement learning from AI feedbackRLAIF
• Reinforcement learning from human feedbackRLHF
• Reward model
• ROC curveReceiver operating characteristic
• Self-supervised learning
• Self-training
• Semi-supervised learning
• Softmax
• Spectral clustering
• Stacking
• Student model
• Supervised fine-tuningSFT
• Supervised learning
• Support vector machine
• Synthetic data
• Teacher model
• Tensor
• Time-series forecasting
• Train-test split
• Training run
• Transfer learning
• Unsupervised learning
• Value function
• Voting classifier
• Zero-shot learning