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Supervised Learning
The main goal in supervised learning is to learn a model from labeled training data that allows us to make predictions about unseen or future data. Examples:
Unsupervised Learning
Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets without human intervention, in contrast to supervised learning where labels are provided along with the data.
Reinforcement Learning
Reinforcement learning is a type of machine learning technique where a computer agent learns to perform a task through repeated trial and error interactions with a dynamic environment. Examples:
Deep Learning
Deep learning allows machines to solve complex problems even when using a data set that is very diverse, unstructured and inter-connected. Examples:
Machine Learning
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Artificial Intelligence
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Data Science
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