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  • PSTAT 231

    • Introduction to Statistical Machine Learning . PSTAT 231

    Statistical Machine Learning is used to discover patterns and relationships in large data sets. Topics will include: data exploration, classification and regression trees, random forests, clustering and association rules. Building predictive models focusing on model selection, model comparison and performance evaluation. Emphasis will be on concepts, methods and data analysis; and students are expected to complete a significant class project, individual or team based, using real world data.

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    Prerequisites: PSTAT 120A-B; and PSTAT 126 with a minimum grade of C or better.

    4

    Units

    Optional

    Grading

    1, 2, 3

    Passtime

    Graduate students only

    Level Limit

    Letters and science

    College
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    Lecture
    TD-W 1701
    T R
    15:30 PM - 16:45 PM
    1 / 25
    Enrollment Trends
    Past Enrollment Trends (9)
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    Spring 2024 . Coburn K M
    NH 1006
    T R
    15:30 PM - 16:45 PM
    Fall 2024 . Baracaldo Lan
    LSB 1001
    T R
    17:00 PM - 18:15 PM
    Grading Trends (32)
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    PSTAT 231 Yu G Fall 2025 Total: 22
    PSTAT 231 Coburn K M Spring 2025 Total: 20
    Other PSTAT 231 Offerings
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    PSTAT 231
    5 / 25 Enrolled
    Introduction to Statistical Machine Learning
    Katie Coburn 3.1
    T R
    15:30 PM - 16:45 PM
    PSTAT 231
    2 / 25 Enrolled
    Introduction to Statistical Machine Learning
    Katie Coburn 3.1
    T R
    17:00 PM - 18:15 PM
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