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Winter 2020: Applied Machine Learning for Affective Computing

Winter 2020: Applied Machine Learning for Affective Computing

Course No:
EECS 498-005 / EECS 598-010
Credit Hours:
3 credits
Instructor:
Emily Mower Provost
Prerequisites:
EECS 281 and (MATH 214 or MATH 217 or MATH 296 or MATH 417) or graduate standing

This course covers the concepts and techniques that underlie machine learning of human behavior across multiple interaction modalities. Topics include: speech/text/gestural behavior recognition through applications of machine learning, including deep learning. Fluency in a standard object-oriented programming language is assumed. Prior experience with speech or other data modeling is neither required nor assumed.

More info (pdf)