In this course, students are divided into teams to survey the field of AI applications, make presentations to the faculty and fellow students on areas that are ripe for AI development, and develop a product proposal, which will be carried through for the semester-long term project. Students learn and build deep learning applications using TensorFlow and Python. Topics include supervised learning, feed-forward neural networks, flow graphs, dynamic computational graphs, convolutional neural networks, and recurrent neural networks. Students will use high-level tools to engineer functioning machine learning models.
Grad Scheme
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