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Tidymodels - The Machine Learning Framework For R
Rating: 4.4 out of 5(20 ratings)
72 students

Tidymodels - The Machine Learning Framework For R

Jumpstart your machine learning journey with the most powerful machine learning framework in the R programming language.
Created byAmber Krause (MBA)
Last updated 3/2024
English

What you'll learn

  • Start your machine learning journey with the R programming language.
  • Tune machine learning model hyperparameters using Tidymodels.
  • Preprocess your data using recipes.
  • Evaluate and compare multiple machine learning algorithms to deliver the most accurate model.

Course content

1 section • 10 lectures • 1h 25m total length

  • Introduction2:03
  • Key Concepts of Tidymodeling6:36
  • Installing Tidymodels and "Spending Your Data"5:53
  • Preprocessing Data Using Recipes10:10

    Explore the recipes function in Tidymodels to preprocess data, create dummy variables, and normalize predictors, building reusable preprocessing pipelines from the training data.

  • Creating Machine Learning Model Specifications8:24
  • Making Predictions Using Workflows12:38
  • Tuning Model Hyperparmeters12:29
  • Evaluating Multiple Machine Learning Models with Workflow Sets11:11
  • Tuning Multiple Models with Workflow Maps15:46

    Explore Tidymodels' ability to tune multiple models and pre-processing steps with a workflow map, compare random forest and k-nearest neighbors, and select the best hyperparameters for final fitting.

  • Course Conclusion0:40

    Celebrate the journey from simple data processing with recipes to building, tuning, and automating multiple models with varied pre-processing steps using Tidymodels.

Requirements

  • This course assumes a basic level of experience with the R programming language and a general familiarity with machine learning concepts.
  • This course is designed to help you implement machine learning using the Tidymodels framework in R. This course will NOT teach basic R concepts or the reasoning behind machine learning.

Description

Welcome to Machine Learning With Tidymodels. This course is designed to show you how to use R's fast, flexible, and powerful machine learning framework known as Tidymodels. Tidymodels is the up-to-date successor to the previous caret machine learning package and offers a simple, intuitive way to make your machine learning tasks a breeze. In this course you will learn the most important features offered by Tidymodels including


  • How to split data into testing and training sets

  • Save time by preprocessing your data using the recipes functions

  • Create workflows to fit models to training data and make predictions

  • Compare multiple models and preprocessing steps using powerful workflow sets

  • Evaluate the accuracy of your machine learning models

  • Automatically tune your models to deliver optimum predictive performance


This course is designed to be an introduction to Tidymodels, so I will provide examples and explanations for all of the topics discussed in the course. Although this course is designed to introduce you to Tidymodels and Machine Learning using R, this is NOT designed to teach you the basics of R or the basics of machine learning. I assume that you have a basic familiarity with both the R programing language and the general concepts of machine learning prior to starting the course. The focus of this course is on showing you how to use the powerful features provided by the Tidymodels package.


If you want to learn more about how to simplify your machine learning process using Tidymodels, then this is the course for you! Let's start learning.

Who this course is for:

  • Anyone seeking to learn more about the Tidymodels machine learning framework used in the R programming language.

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