Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
Machine Learning
incremental-learning
A machine learning approach that updates models continuously with new data without retraining from scratch.
Machine Learning
Machine Learning
A subset of AI that enables systems to learn from data and improve over time.
Machine Learning
modalities
Different forms or types of data used in machine learning, such as text, images, or audio.
Machine Learning Operations
Model Deployment
The process of making a trained machine learning model available for use in a production environment.
Machine Learning
Model Generalization
The ability of a machine learning model to perform well on unseen data.
Machine Learning
Model Training
The process of teaching a machine learning model to make predictions based on data.
Machine Learning
model-complexity
A measure of the capacity of a machine learning model to fit a wide variety of functions.
optimization
model-compression
Techniques for reducing the size and complexity of machine learning models while maintaining performance.
machine-learning
model-interpretation
The process of understanding and explaining the predictions made by a machine learning model.
modeling
model-trained
The process of training a machine learning model using data.
machine-learning
multi-task-learning
An approach in machine learning where multiple tasks are learned simultaneously, sharing representations.
machine learning
one-shot-learning
A machine learning approach that enables a model to learn information about object categories from a single training example.
data-preprocessing
pipeline
A sequence of data processing steps for machine learning workflows.
quantum computing
quantum-machine-learning
An interdisciplinary approach merging quantum computing with machine learning techniques.
Machine Learning
Reinforcement Learning
A type of machine learning focused on teaching agents to make decisions by maximizing cumulative rewards.
Machine Learning
Self-supervised Learning
A type of machine learning where the model learns from unlabeled data by generating its own labels.
Machine Learning
Supervised Learning
A type of machine learning where the model learns from labeled data.
Data Science
synthetic-data-generation
The process of creating artificial data that mimics real-world data for training machine learning models.
Learning Techniques
Transfer Learning
A machine learning technique where a model developed for one task is reused for a different but related task.
Machine Learning
Unsupervised Learning
A type of machine learning that deals with data that has no labels, aiming to find hidden patterns or intrinsic structures.
Machine Learning
Zero-shot Learning
A machine learning approach where the model predicts classes that it has not seen during training.