Glossary
Dec 4, 2025
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5 min read
Semi-supervised Learning combines elements of both supervised and unsupervised learning by utilizing both labeled and unlabeled data during training.
Classification is the task of predicting which category or class a new instance belongs to, learned from labeled historical examples.
Dec 3, 2025
Unsupervised Learning encompasses a class of machine learning methods that automatically discover hidden patterns, structures, and relationships within unlabeled data—datasets where ground truth target variables are not provided.
Supervised Learning represents a fundamental machine learning paradigm where algorithms learn to predict outputs from inputs by training on labeled data—datasets where the correct answer is explicitly provided for each training example.
Deep Learning represents a specialized subset of machine learning that utilizes artificial neural networks with multiple layers (typically three or more) to automatically learn hierarchical representations of data.
Dec 2, 2025
6 min read
Machine Learning represents a method that helps machines learn from data and improve at performing tasks without being explicitly programmed for every scenario.
4 min read
An algorithm represents an unambiguous specification of how to solve a class of problems, capable of performing calculation, data processing, and automated reasoning tasks.
Artificial General Intelligence represents a theoretical form of AI that demonstrates a broad range of problem-solving, creativity, and adaptability comparable to human intelligence.
Sep 9, 2025
Artificial Intelligence, a term coined in 1955 by Stanford University computer science professor John McCarthy, was originally defined as "the science and engineering of making intelligent machines"
