machine learning

Meanings

• noun

  A subfield of artificial intelligence that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

  - "Machine learning algorithms are used to analyze large datasets and make predictions or decisions."
  - "The machine learning model was trained on a dataset of customer behavior to identify patterns and make recommendations."

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Variants

List of all variants of machine learning that leads to same result
machine learning , reinforcement machine learning , supervised machine learning , unsupervised machine learning

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Etymology

origin and the way in which meanings have changed throughout history.

The term 'machine learning' was first coined by Arthur Samuel in 1959.

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Trivia

Any details, considerations, events or pieces of information regarding the word

1. Machine learning is based on the idea that systems can learn from data, just as humans learn from experience.

2. One of the earliest applications of machine learning was in the game of checkers, where a program was able to learn to beat a human opponent.

3. Machine learning algorithms are used in various industries, including finance, healthcare, and marketing.

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Related Concepts

informations on related concepts or terms closely associated with the word. Discuss semantic fields or domains that the word belongs to

1. Artificial Intelligence: Machine learning is a subfield of artificial intelligence, which focuses on creating systems that can learn from data.

2. Deep Learning: Deep learning is a subset of machine learning that uses neural networks with multiple layers to learn and make predictions.

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Culture

Any cultural, historical, or symbolic significance of the word. Explore how the word has been used in literature, art, music, or other forms of expression.

Machine learning has been a popular topic in science fiction and has been portrayed in various ways, from advanced AI systems to sentient machines.

How to Memorize "machine learning"

1. visualize
   

   - Imagine a computer system that is able to learn from data and improve its performance over time.
   - Visualize a flowchart of a machine learning algorithm, from data input to output.

2. associate
   

   - Associate machine learning with large datasets and complex algorithms.
   - Associate machine learning with artificial intelligence and intelligent systems.

3. mnemonics
   

   - M-Machine, L-Learning: Machine Learning is a system that learns.
   - M-Model, L-Learning: Machine Learning is a model that learns.

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