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Content

This online course explores the essentials of machine learning and algorithms to help improve learning from data without human intervention.


Topics of the course include: classification and regression, clustering methods, sequential models, matrix factorization, topic modeling and model selection.


Methods include: linear and logistic regression, support vector machines, tree classifiers, boosting, maximum likelihood and MAP inference, EM algorithm, hidden Markov models, Kalman filters, k-means, Gaussian mixture models, among others.

Columbia University

Teacher: John W. Paisley
Provided by: edX
Course language: English
Fees: free course
Level: advanced
Certificate possible? (fee)
Format: MOOC/online course

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