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Brown University

 

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Spring 2020
Sep 17, 2019
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CSCI 2470 - Deep Learning
Deep learning is the name for a particular version of neural networks--a version that emphasizes multiple layers of networks. Deep leaning, plus the specialized techniques that it has inspired (e.g. convolutional features and word embeddings) have lead to rapid improvements in many applications such as computer vision, machine translation, and computer Go. This course intends to give students a practical understanding of deep learning as applied in these and other areas. It also teaches the Tensorflow programming language for the expression of deep leaning algorithms. A final project will implement an advanced piece of work in one of these areas. Pre Requisites: A basic programming course: (CSCI 0150, 0170 or 0190) A linear algebra course: (CSCI 0530, MATH 0520 or 0540) A stats / probability course: (CSCI 0220, 1450, 0450, MATH 1610, APMA 1650 or 1655)
1.000 Credit hours
1.000 Lecture hours

Levels: Graduate, Undergraduate
Schedule Types: Primary Meeting

Computer Science Department

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

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