Concept graph
Generative AI and LLM glossary
Clear AI definitions with practical context, examples, and links to related models, tools, and concepts.
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.