Deep Learning
Instructor(s): Lynn Kaack
Abstract
As the fastest growing subfield of machine learning, deep learning is the technology behind facial recognition, machine translation, AlphaGo, and many other well-known applications. As policy makers are beginning to regulate machine learning, technical understanding of deep learning in public policy is invaluable. In policy research and analysis, deep learning has only recently started to be applied. In this course, students will learn the main theoretical concepts of (deep) neural networks, and get introduced to applications in computer vision, natural language processing and other areas. Students will gain hands-on experience by training and testing their own models in policy-relevant applications. The main objective of this course is to enable students to scope out new meaningful and robust deep learning applications, and to advise decision makers on strengths and limitations of the technology.
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