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    Supervised Machine Learning: Regression

    BY
    IBM via Coursera

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    Lavel

    Intermediate

    Mode

    Online

    Duration

    2 Weeks

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based
    Learning efforts 10 Hours Per Week

    Course and certificate fees

    The course fees for Supervised Machine Learning: Regression is -

    HeadAmount
    1 monthRs. 3,256
    3 monthRs. 6,512
    6 monthRs. 9,769
    certificate availability

    Yes

    certificate providing authority

    Coursera

    The syllabus

    Module 1: Introduction to Supervised Machine Learning and Linear Regression

    Videos
    • Welcome/ Introduction Video
    • Introduction to Supervised Machine Learning: What is Machine Learning?
    • Introduction to Supervised Machine Learning: Types of Machine Learning
    • Supervised Machine Learning for Interpretation and Prediction
    • Regression and Classification Examples
    • Introduction to Linear Regression
    • Linear Regression Demo - Part 1
    • Linear Regression Demo - Part 2
    • Linear Regression Demo - Part 3
    Readings
    • Course Prerequisites
    • Linear Regression Demo (Activity)
    • Summary/Review
    Practice Exercises
    • Check for Understanding
    • End of Module Quiz

    Module 2: Data Splits and Cross Validation

    Videos
    • Training and Test Splits
    • Training and Test Splits Lab - Part 1
    • Training and Test Splits Lab - Part 2
    • Training and Test Splits Lab - Part 3
    • Training and Test Splits Lab - Part 4
    • Cross-Validation
    • Cross-Validation Demo - Part 1
    • Cross-Validation Demo - Part 2
    • Cross-Validation Demo - Part 3
    • Cross-Validation Demo - Part 4
    • Cross-Validation Demo - Part 5
    • Polynomial Regression
    Readings
    • Training and Test Splits Demo
    • Cross-Validation Demo
    • Summary/Review
    Practice Exercises
    • Check for Understanding
    • End of Module Quiz

    Module 3: Regression with Regularization Techniques: Ridge, LASSO, and Elastic Net

    Videos
    • Bias Variance Trade off
    • Regularization and Model Selection
    • Ridge Regression
    • LASSO Regression
    • Polynomial Features and Regularization Demo - Part 1
    • Polynomial Features and Regularization Demo - Part 2
    • Polynomial Features and Regularization Demo - Part 3
    • Further details of regularization
    • Details of Regularization - Part 1
    • Details of Regularization - Part 2
    • Details of Regularization - Part 3
    Readings
    • Polynomial Features and Regularization Demo
    • Details of Regularization Demo
    • Summary/Review
    Practice Exercises
    • Check for Understanding
    • End of Module Quiz

    Instructors

    Mr Mark J Grover

    Mr Mark J Grover
    Digital Content Delivery Lead
    IBM

    Mr Miguel Maldonado

    Mr Miguel Maldonado
    Machine Learning Curriculum Developer
    IBM

    Ms Svitlana Kramar

    Ms Svitlana Kramar
    Data Science Content Developer
    IBM

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