15.680 Machine Learning: Algorithms, Applications, and Computation
Develops key algorithms for machine learning with emphasis on data, applications, and computation. Includes regression, classification, support vector machines, unsupervised learning, algorithms for missing data, principal component analysis, sparse recovery, factor analysis, robustness, deep learning, and reinforcement learning. Restricted to Master of Business Analytics and LGO students.
This class has no prerequisites.
15.680 will be offered this semester (Fall 2017). It is instructed by D. Bertsimas.
Lecture occurs 4:00 PM to 5:30 PM on Mondays and Wednesdays in E51-315.
This class counts for a total of 6 credits.
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