DS 623 Machine Learning in Data Science
This course introduces machine learning techniques and methods. The coverage includes applied machine learning for the data scientist, the issue of the dimensionality of data, the task of data clustering, clusters evaluation, supervised approaches for building predictive models, data generalization (e.g., cross- validation and over-fitting). This course coverage includes advanced techniques, such as developing ensembles methods, and predictive models practical limitations.