Concept graph
Generative AI and LLM glossary
Clear AI definitions with practical context, examples, and links to related models, tools, and concepts.
Evaluation
Faithfulness
Faithfulness is whether every claim in a generated answer is supported by the supplied evidence.
Data Preparation
Feature Engineering
The process of selecting, modifying, or creating features from raw data.
Model Interpretation
Feature Importance
A measure of how much a feature contributes to the predictive power of a model.
Machine Learning
Feature Mapping
The process of transforming input features into a more suitable format for modeling.
Data Preprocessing
Feature Scaling
The process of standardizing or normalizing features so they contribute equally to the model.
Machine Learning
Feature Vector
A numerical representation of an object's characteristics used in machine learning.
Data Processing
feature-extraction
The process of transforming raw data into a set of usable characteristics for model training.
Data Processing
feature-selection
The process of selecting a subset of relevant features for model training.
Machine Learning
Federated Learning
A machine learning approach that allows models to be trained across decentralized devices or servers holding local data samples.
Machine Learning
few-shot-learning
A machine learning paradigm that trains models with very few labeled examples.
Training
Fine-tuning
Fine-tuning continues training a pretrained model on a smaller, task-specific dataset so it follows that task more reliably.
Agents
Function calling
Function calling is the API pattern where a model returns a named function and arguments for the application to execute.