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CSCI 2470 - Deep Learning |
Deep Learning belongs to a broader family of machine learning methods. It is a particular version of artificial neural networks that emphasizes learning representation with multiple layers of networks. Deep Learning, plus the specialized techniques that it has inspired (e.g. convolutional neural networks, recurrent neural networks, and transformers), have led to rapid improvements in many applications, such as computer vision, machine learning, sound understanding, and robotics. This course gives students an overview of the prominent techniques of Deep Learning and its applications in computer vision, language understanding, and other areas. It also provides hands-on practice of implementing deep learning algorithms in Python. A final project will implement an advanced piece of work in one of these areas. Prerequisites: basic programming: (CSCI 0150, 0170, 0190); linear algebra: (CSCI 0530, MATH 0520, 0540); stats/probability: (CSCI 0220, 1450, 0450, MATH 1610, APMA 1650, 1655)
0.000 OR 1.000 Credit hours 0.000 OR 1.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Discussion Section/Conference, Primary Meeting Computer Science Department Restrictions: Must be enrolled in one of the following Levels: Graduate |
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