MSDS 422-DL Practical Machine Learning.

The course introduces machine learning with business applications. It provides a survey of statistical and machine learning algorithms and techniques including the machine learning framework, regression, classification, regularization and reduction, tree-based methods, unsupervised learning, and fully connected, convolutional, and recurrent neural networks. Students implement machine learning models with open-source software for data science. They explore data and learn from data, finding underlying patterns useful for data reduction, feature analysis, prediction, and classification. Recommended prior programming experience or 430-DL Python for Data Science. Prerequisites: (1) MSDS 400-DL Math for Modelers, (2) MSDS 401-DL Applied Statistics with R.

Students benefit by taking the Python Learning Studio and MSDS 430 Python for Data Science prior to taking this course.

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