BUAN512

Machine Learning is at the heart of big data mining and predictive analytics. Students learn and apply the fundamental methods at the core of modern machine learning to data mining and predictive analytics. Topics covered include: the use of the sci-kit learning, NumPy and matplotllib libraries to generate a variety of machine learning algorithms including KNN, Linear Models, Naive Bayes Classifiers, Decision Trees, Kernelized SVM and Neural Networks; the creation of models using techniques like preprocessing and scaling, dimensionality reduction, feature engineering, manifold learning and clustering; the generation of algorithm chains and pipelines to optimize the performance of their models. Students are also expected to know how to present their modeling findings and recommendations to non-technical stakeholders. As such there is a final project assessment that will help to hone these skills. Prerequisites: BUAN 500 and BUAN 501. Offered: Fall, Winter, Spring, Summer.

-