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This lecture provides an in-depth overview of ensemble learning in machine learning projects, focusing on neural networks such as perceptrons and multi-layer perceptrons, as well as support vector machines. The session explores the applications of neural networks in various industries and emphasizes learning from text data. Reference is also made to the previous lecture where the choice of a single hypothesis was discussed as part of the learning process.
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