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Today, in all domains of science and technology it is necessary to have computer systems able to work autonomously and to build knowledge from raw data coming from the Web or from huge data-bases. Machine Learning concerns the study and implementation of systems able to perform these tasks. The intent of this course is to propose a broad introduction to field of Machine Learning, including discussions of each of the major approaches, symbolic and numeric, currently being investigated and achievements they can be done. Another goal is to compare the advantages and drawbacks of these various methods and to explain under which conditions each is most appropriate.

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