Machine Learning and Deep Learning for Data Science

Course Overview

Study of supervised and unsupervised algorithms for machine learning. Emphasis on formulating, choosing, applying, implementing, evaluating machine learning models to capture key patterns exhibited in cross-sectional data, time-series data, and longitudinal data. Considerations of model complexity, results interpretations, and implementation in real-world applications using Python and associated packages.


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