The purpose of the course is to provide the participants with basic knowledge and conception of supervised and unsupervised machine learning and how they can be applied for classification and regression.
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Fundamentals of Machine Learning.
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Mathematics for Machine Learning.
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Supervised Machine Learning for Classification: kNN, DT, Linear Models.
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Supervised Machine Learning for Regression: Linear Regression.
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Unsupervised Machine Learning: K-Means, Fuzzy c-Means.