Concept graph
Generative AI and LLM glossary
Clear AI definitions with practical context, examples, and links to related models, tools, and concepts.
Machine Learning
batch-learning
A learning method where the model is trained on a fixed dataset in one go.
AI Ethics
Bias Mitigation
Techniques and strategies aimed at reducing bias in AI models and datasets.
Data Preprocessing
Data Imbalance
A situation in which classes in a dataset are not represented equally.
Data Processing
data-sampling
The process of selecting a subset of data from a larger dataset.
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.
privacy technology
differential-privacy
A method to ensure that individual data points cannot be identified in datasets.
Data Processing
dimensionality-reduction
The process of reducing the number of features in a dataset while preserving important information.
Training
Fine-tuning
Fine-tuning continues training a pretrained model on a smaller, task-specific dataset so it follows that task more reliably.
data-quality
noisy-labels
Labels in a dataset that are inaccurate or wrong, often leading to misguidance in model training.
Data Science
Principal Component Analysis (PCA)
A dimensionality reduction technique used to simplify datasets while preserving variance.
Machine Learning
scalable-dot-product-attention
An efficient variant of attention mechanism designed for large datasets.
Data Sampling
stratified-sampling
A sampling method that ensures representation from different subgroups in a dataset.