Concept graph
Generative AI and LLM glossary
Clear AI definitions with practical context, examples, and links to related models, tools, and concepts.
Data Processing
Data Wrangling
The process of cleaning and organizing raw data into a desired format.
Data Security
data-encryption
The process of converting data into a coded format to prevent unauthorized access.
Data Management
data-integration
The process of combining data from different sources to provide a unified view.
Data Management
data-migration
The process of transferring data between storage types or formats.
Data Analysis
data-mining
The process of discovering patterns and knowledge from large amounts of data.
Data Management
data-quality
A measure of the condition and reliability of data used in analysis and decision-making processes.
Data Processing
data-sampling
The process of selecting a subset of data from a larger dataset.
Data Processing
data-sourcing
The process of obtaining and collecting data from various sources.
Data Presentation
data-visualization
The graphical representation of information and data to communicate insights clearly.
Data Management
Dataset
A structured collection of data used for analysis and training machine learning models.
Data Management
Dataset Splitting
The process of dividing a dataset into training, validation, and test sets.
Machine Learning
Decision Tree
A decision support tool that uses a tree-like model of decisions.
Machine Learning
Deep Learning
A subfield of machine learning that uses neural networks with many layers.
Media Technology
deepfake
A synthetic media in which a person in an image or video is replaced with someone else's likeness.
privacy technology
differential-privacy
A method to ensure that individual data points cannot be identified in datasets.
Models
Diffusion
Diffusion models generate images or other media by iteratively denoising from noise toward a sample that matches a prompt or condition.
Simulation
digital-twin
A virtual representation of a physical object or system used for simulation and analysis.
Data Processing
dimensionality-reduction
The process of reducing the number of features in a dataset while preserving important information.
Computing
Distributed Computing
A computing paradigm where processing is distributed across multiple machines or nodes.
Machine Learning
distributed-learning
A machine learning paradigm where the training data is distributed across multiple devices or nodes.
Machine Learning
domain-adaptation
A technique in machine learning that aims to improve model performance on a target domain by leveraging labeled data from a related source domain.
Regularization
Dropout
A regularization technique used to prevent overfitting in neural networks by randomly deactivating a fraction of neurons during training.
algorithm-design
dynamic-programming
A method for solving complex problems by breaking them down into simpler subproblems.
Computing
edge computing
Edge computing is a computing paradigm that brings computation and data storage closer to the location of the data source.