Glossary Core Concepts 1 min read

Machine Learning

Also known as: ML

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.

ML, statistical learning, pattern recognition, predictive modeling, classification, regression, clustering, dimensionality reduction, feature engineering, model training, model evaluation, cross-validation, hyperparameter tuning

Sources & References

1
Machine Learning - Stanford Online

Stanford University

2
An Introduction to Machine Learning

IBM

3
Machine Learning for Beginners Curriculum

Microsoft

Documentation

Related Terms

Artificial Intelligence (AI)

The simulation of human intelligence processes by computer systems, including learning, reasoning, self-correction, and the ability to perform tasks that typically require human cognition.

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.

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.

Supervised Learning

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.

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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