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Machine Learning is a subset of artificial intelligence (AI) that involves the development of algorithms and statistical models. These algorithms enable computer systems to learn and improve their performance on a specific task over time, without being explicitly programmed. In essence, machine learning allows machines to recognize patterns in data and make predictions or decisions based on those patterns.
There are different types of machine learning approaches, including supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, the algorithm is trained on labeled data, where the input and corresponding output are provided, allowing the algorithm to learn the mapping function. Unsupervised learning involves clustering and association and does not require labeled output data. Reinforcement learning focuses on making sequences of decisions by interacting with an environment to achieve maximum cumulative reward.
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