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Course Discription |
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Introduction to Python programming; introduction to machine learning; formulation of supervised and unsupervised learning problems; regression and classification; data normalization and feature engineering; selection of loss functions and their impact on learning; regularization and its role in controlling complexity; validation and preprocessing; robustness to outliers; basic numerical applications; and experiments on data from a wide range of engineering and other disciplines. |