Glossary Model Training 1 min read

Supervised Learning

Also known as: Supervised ML

A machine learning paradigm where models are trained on labeled datasets containing input-output pairs, learning to map inputs to correct outputs for prediction and classification tasks.

Labeled data, classification, regression, training labels, ground truth, annotation, labeled examples, prediction, model accuracy, overfitting, underfitting, generalization, train-test split, validation, supervised training

Sources & References

1
Supervised Learning - Stanford CS229

Stanford University

2
Supervised Learning with scikit-learn

scikit-learn

Documentation
3
What is Supervised Learning?

Google Cloud

Related Terms

Deep Learning

A subset of machine learning based on artificial neural networks with multiple layers (deep architectures) that can learn hierarchical representations of data for complex pattern recognition.

Machine Learning

A subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed, using algorithms that identify patterns in data.

Neural Network

A computing system inspired by biological neural networks, consisting of interconnected nodes (neurons) organized in layers that process information using learnable weights and activation functions.

Training Data

The curated dataset used to train machine learning models, whose quality, diversity, size, and representativeness directly determine the model's capabilities and limitations.
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