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This document discusses different machine learning algorithms including supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Supervised learning uses labeled data to generate predictions, unsupervised learning finds patterns in unlabeled data through clustering and visualization, semi-supervised learning combines labeled and unlabeled data, and reinforcement learning uses rewards to learn behaviors. The document provides examples of applications for each type of learning such as price prediction, image clustering, and autonomous vehicles.
