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Computers learn with data.
Computer learn description
Computers learn by processing and analyzing large amounts of data using complex algorithms and statistical models. This process is known as machine learning.
Machine learning algorithms can be classified into three main categories: supervised learning, unsupervised learning, and reinforcement learning.
Supervised learning involves providing the computer with labeled data, where the desired output is already known, and the computer learns to recognize patterns and make predictions based on that data. Examples of supervised learning include image recognition and language translation.
Unsupervised learning involves giving the computer unlabeled data and allowing it to find patterns and structure on its own. This can be useful for tasks such as clustering and anomaly detection.
Reinforcement learning involves training a computer to make decisions based on feedback from its environment.