Han Liu @ Computer Science, Northwestern University

EECS496 Section 7: Advanced Topics on Deep Learning

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Study of advanced topics of current interest in the field of deep learning, with an emphasis on understanding the network architecture of the pre-trained deep learning models. Selected topics from the following areas will be covered, with an emphasis on practical applications: computer vision, speech recognition, natural language processing, reinforcement learning, and deep learning tools.

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EECS496/396 Section 5: Statistical Machine Learning

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This course introduces statical machine learning methods from a theoretical perspective. Topics include the maximum likelihood inference, regularization principle, risk minimization framework, cross-validation, high dimensional inference and nonparametric methods.

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STATS301 Section 6: Data Science Capstone Project

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By completing this capstone project the students will get an opportunity to apply the knowledge and skills in data science to some real industrial projects. In particular, it will test their skills in data acquisition, data visualization, data wrangling, data organization, data modeling and data analysis. Unlike the other courses in the Data Science series, in this course, the students are expected to explore some projects that are more real and open-ended.

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Reading Group

We have biweekly reading group. The topics of this quarter include conversational AI, object detection and optimal character recognition, deep reinforcement learning, robotics operating system.

Get In Touch

Department of Computer Science
Mudd Hall 3119
Northwestern University
Evanston, IL 60201
Phone: +847 491 2793
Email: hanliu@northwestern.edu