Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
machine learning
one-shot-learning
A machine learning approach that enables a model to learn information about object categories from a single training example.
Knowledge Representation
ontologies
Formal representations of a set of concepts within a domain and the relationships between those concepts.
Knowledge Representation
ontology
An ontology is a formal representation of a set of concepts within a domain.
Data
open weights
open weights is a core generative-AI concept used across modeling, product, and governance discussions.
machine learning
out-of-distribution-generalization
The ability of a model to perform well on unseen data that is different from the training set.
data-analysis
outlier
An observation point that is distant from other observations in the dataset.
Data Analysis
Outlier Detection
The identification of data points that deviate significantly from the majority of data.
Modeling
Overfitting
A modeling error that occurs when a model learns noise and details from the training data.
Product
pgvector
pgvector is a core generative-AI concept used across modeling, product, and governance discussions.
Training
PII detection
PII detection is a core generative-AI concept used across modeling, product, and governance discussions.
data-preprocessing
pipeline
A sequence of data processing steps for machine learning workflows.
Inference
positional encoding
positional encoding is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
PPO
PPO is a core generative-AI concept used across modeling, product, and governance discussions.
evaluation
precision-recall-curve
A graphical representation of a model's trade-off between precision and recall.
Data Analysis
predictive-analytics
The use of statistical techniques to forecast future events based on historical data.
Safety
preference optimization
preference optimization is a core generative-AI concept used across modeling, product, and governance discussions.
Data Science
Principal Component Analysis (PCA)
A dimensionality reduction technique used to simplify datasets while preserving variance.
data-analysis
principal-component-analysis
A dimensionality reduction technique that transforms data into a set of orthogonal components.
Data
privacy redaction
privacy redaction is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
prompt engineering
Prompt engineering is the practice of structuring instructions, context, and formats to get reliable model behavior.
Machine Learning
pruning
The process of removing unnecessary parameters from a neural network to create a more efficient model.
Inference
QLoRA
QLoRA is a core generative-AI concept used across modeling, product, and governance discussions.
Inference
quantization
quantization is a core generative-AI concept used across modeling, product, and governance discussions.
Computing
Quantum Computing
A type of computing that utilizes quantum mechanics to process information at unprecedented speeds.