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Machine-Learning

About

Quote

"the field of study that gives computers the ability to learn without explicitly being programmed" - Arthur Samuel1

Machine Learning (ML) is sub-field of Artificial-Intelligence, that deals with software algorithms for two purposes.2 1. Detect and learn patterns from a dataset. (The training / learning part) 2. Make predictions on unseen / undisclosed data without being explicitly programmed.

ML is mainly concerned with making the Machine (computer) learn - patterns from available data to make predictions (guess-timations). How accurate these predictions are, depends highly on the quality of training data, the methodology used, and the amount of human intervention during the training / learning stage.

Machine Learning Model

  • A Machine-Learning-Model is the product of the Machine Learning process(es).
  • It describes the algorithm / system that has been trained on data, to recognize patterns and/or make predictions.

Supervised Learning

Un-Supervised Learning

See Also

  1. Artificial-Intelligence
  2. [[Pre-Trained-Models]]
  3. [[Deep-Learning]]
  4. [[Neural-Networks]]
  5. [[Generative-AI]]

References

  1. Machine learning, explained, by Sara Brown on mitsloan.mit.edu (21 April 2021) ↩

  2. What is Machine Learning? Definition, Types, Tools & More, by Matt Crabtree on datacampo.com (July 2023) ↩