INFO521

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INFO521 - Introduction to Machine Learning

School of Information Graduate UA - UA General

Course Description

Machine learning describes the development of algorithms which can modify their internal parameters (i.e., \"learn\") to recognize patterns and make decisions based on example data. These examples can be provided by a human, or they can be gathered automatically as part of the learning algorithm itself. This course will introduce the fundamentals of machine learning, will describe how to implement several practical methods for pattern recognition, feature selection, clustering, and decision making for reward maximization, and will provide a foundation for the development of new machine learning algorithms.

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 - COGS (Cognitive Science), GIDP - GC (Global Change), GIDP - NRSC (Neuroscience), GIDP - SLAT (Sec. Lang. Acquisition & Teach), GIDP - STATD (Statistics and Data Science)

May be convened with

ISTA421

Name

Lecture

Workload Hours

3

Optional Component

No

Typically Offered Main Campus

Fall