Course overview

In this course, you’ll learn how to select the appropriate features for your linear regression model to yield the best performance, as well as how to use gradient descent, an optimization algorithm used to minimize a function by iteratively moving in the direction of steepest descent. You’ll also learn how to fit a model using the Ordinary Least Squares (OLS) algorithm, as well as why OLS works.

Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. At the end of the course, you’ll complete a project to predict housing prices using the AmesHousing dataset. This project is a chance for you to combine the skills you learned in this course and practice a machine learning workflow.

Key skills

    • Making predictions using the linear regression machine learning model
    • Using gradient descent
    • Selecting, cleaning, and transforming features
    • Fitting a linear regression model

Course outline

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Projects in this course

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