Machine Learning is related to the design and study of systems that can learn by automatically extracting information from data. An example of application is classification, which consists of assigning an input data to a class.
This course offers a broad introduction to Machine Learning and its applications to real problems. A subset of the following is covered: principal component analysis, linear discriminant analysis, bayesian decision theory, density estimation, ..., support vector machines, deep neural networks.
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