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Machine Learning

A branch of AI that enables systems to learn from data without being explicitly programmed. Instead, algorithms can analyze and learn from patterns in data.

One minute overview

Machine learning is a subset of artificial intelligence (AI) that involves training algorithms to make predictions or decisions based on data. Neural networks are a subset of machine learning but are not necessary to use when training an algorithm.

Machine learning algorithms can be divided into three main categories: supervised learning, unsupervised learning, and reinforcement learning.

Supervised learning involves training a model on a labeled dataset, where the desired output is known for each input. The model learns to map inputs to outputs by minimizing the difference between the predicted output and the actual output.

Unsupervised learning involves training a model on an unlabeled dataset, where the desired output is not known. The model learns to identify patterns and relationships in the data without any specific guidance.

Reinforcement learning involves training a model to make decisions in a dynamic environment, where the model receives feedback in the form of rewards or penalties based on its actions.

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