Machine Learning Algorithms
Machine learning algorithms are a set of statistical models and techniques that enable computer systems to learn from data and improve their performance on a specific task without being explicitly programmed. These algorithms use various mathematical and statistical models to identify patterns and relationships in data, and then use these patterns to make predictions or decisions. Machine learning algorithms can be broadly classified into three categories: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning algorithms learn from labeled data, where the correct output is already known. Unsupervised learning algorithms learn from unlabeled data, where the correct output is not known. Reinforcement learning algorithms learn by trial and error, where the system receives feedback in the form of rewards or penalties based on its actions. Machine learning algorithms are widely used in various applications such as image recognition, natural language processing, fraud detection, and recommendation systems.
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