INFO557
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INFO557 - Neural Networks
Course Description
Neural networks are a branch of machine learning that combines a large number of simple computational units to allow computers to learn from and generalize over complex patterns in data. Students in this course will learn how to train and optimize feed forward, convolutional, and recurrent neural networks for tasks such as text classification, image recognition, and game playing.
Min Units
3
Max Units
3
Repeatable for Credit
No
Grading Basis
GRD - Regular Grades A, B, C, D, E
Career
Graduate
Course Attributes
GIDP - STATD (Statistics and Data Science)
May be convened with
ISTA457
Name
Lecture
Workload Hours
3
Optional Component
No
Typically Offered Main Campus
Fall