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Modeling with tidymodels in R

4.7+
25 reviews
Intermediate

Learn to streamline your machine learning workflows with tidymodels.

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4 Hours16 Videos59 Exercises
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Course Description

Tidymodels is a powerful suite of R packages designed to streamline machine learning workflows. Learn to split datasets for cross-validation, preprocess data with tidymodels' recipe package, and fine-tune machine learning algorithms. You'll learn key concepts such as defining model objects and creating modeling workflows. Then, you'll apply your skills to predict home prices and classify employees by their risk of leaving a company.
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In the following Tracks

Machine Learning Fundamentals in R

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Machine Learning Scientist with R

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Supervised Machine Learning in R

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  1. 1

    Machine Learning with tidymodels

    Free

    In this chapter, you’ll explore the rich ecosystem of R packages that power tidymodels and learn how they can streamline your machine learning workflows. You’ll then put your tidymodels skills to the test by predicting house sale prices in Seattle, Washington.

    Play Chapter Now
    The tidymodels ecosystem
    50 xp
    Tidymodels packages
    100 xp
    Creating training and test datasets
    100 xp
    Distribution of outcome variable values
    100 xp
    Linear regression with tidymodels
    50 xp
    Fitting a linear regression model
    100 xp
    Exploring estimated model parameters
    50 xp
    Predicting home selling prices
    100 xp
    Evaluating model performance
    50 xp
    Model performance metrics
    100 xp
    R squared plot
    100 xp
    Complete model fitting process with last_fit()
    100 xp
For Business

GroupTraining 2 or more people?

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In the following Tracks

Machine Learning Fundamentals in R

Go To Track

Machine Learning Scientist with R

Go To Track

Supervised Machine Learning in R

Go To Track

Datasets

Home salesLoansTelecom dataEmployee dataPurchase leads

Collaborators

Collaborator's avatar
Maggie Matsui
David Svancer HeadshotDavid Svancer

Data Scientist

David is a data scientist in the Washington D.C. area where he helps organizations leverage data science and machine learning to solve complex business problems and build data products. He is also an adjunct professor of Business Analytics in the Graduate School of Business at George Mason University where he teaches courses focused on applied statistics, data analysis, machine learning, and database design.
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  • Errin S.
    2 months

    Overall great lesson, with thorough walkthrough of an entire workflow. Very helpful. Few glitches when submitting answers; Usually upon running the last chunk of code it wouldn’t accept it. Had to reload the page then the same answer was accepted.

  • Dan R.
    5 months

    Well designed. However could there be more on Tidy Models?

  • Carlos P.
    6 months

    Very simple but really good.

  • Anders W.
    7 months

    Good balance between videos and Interactive exercisers.

  • Thiago A.
    9 months

    It was a very interesting and didactic course. I found many open source books in the internet, but this one was better or at least in the same level of good learning I found in those books.

"Overall great lesson, with thorough walkthrough of an entire workflow. Very helpful. Few glitches when submitting answers; Usually upon running the last chunk of code it wouldn’t accept it. Had to reload the page then the same answer was accepted."

Errin S.

"Well designed. However could there be more on Tidy Models?"

Dan R.

"Very simple but really good."

Carlos P.

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