Machine Learning and its types

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Machine Learning
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Machine Learning

• Machine learning (ML) is a form of artificial
• intelligence (AI) that allows software programmes
  to improve their prediction accuracy without
  being expressly designed to do so. In order to
  forecast new output values, machine learning
  algorithms use
• historical data as input.

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Machine Learning Example
Machine learning is a branch of artificial
intelligence (AI) that allows computers to learn
and develop on their own without having to be
explicitly programmed. Machine learning is
concerned with the creation of computer
programmes that can access data and learn on
their own.
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Machine Learning Types
Supervised learning
Unsupervised learning
Semi-supervised learning
reinforcement learning
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Supervised learning
Supervised learning, often known as supervised
machine learning, is an artificial intelligence
and machine learning subcategory. Its use of
labelled datasets to train algorithms that
properly categorise data or predict outcomes
defines it.
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Unsupervised learning
Unsupervised learning is a kind of machine
learning in which models are trained on
unlabeled data and then allowed to operate on it
without supervision. This assignment will be
completed by using an unsupervised learning
method to cluster the picture dataset into
groups based on visual similarities.
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Semi-supervised learning
Semi-supervised learning is a machine learning
technique that involves training using a small
quantity of labelled data and a big amount
of unlabeled data. Unsupervised learning (with
no labelled training data) and supervised
learning (with labelled training data) are the
two types of learning (with only labelled
training data).
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Reinforcement learning

• The training of machine learning models to make a
  series of judgments is known as reinforcement
• learning. In an uncertain, possibly complicated
  environment, the agent learns to attain a goal.
  An artificial intelligence encounters a
  game-like
• circumstance in reinforcement learning. Its
  objective is to increase the overall prize as
  much as possible.

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