INFO557

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INFO557 - Neural Networks

School of Information Graduate UA - UA General

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