Learning Algorithm
A learning algorithm is a set of mathematical rules and procedures that enable an artificial intelligence system to learn from data. It is a type of machine learning algorithm that uses statistical techniques to identify patterns in data and make predictions or decisions based on those patterns. Learning algorithms can be supervised, unsupervised, or semi-supervised, depending on the type of data available and the desired outcome. Supervised learning algorithms are trained on labeled data, where the correct output is known, and are used for tasks such as classification and regression. Unsupervised learning algorithms are trained on unlabeled data and are used for tasks such as clustering and anomaly detection. Semi-supervised learning algorithms are a combination of supervised and unsupervised learning and are used when only a small amount of labeled data is available. Learning algorithms are used in a wide range of applications, including natural language processing, computer vision, and predictive analytics.
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