Predict Ideal Diamonds over Good Diamonds using a Random Forest using R

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Coursera Project Network
In this Guided Project, you will:

Complete a random Training and Test Set from one Data Source using an R function.

Practice creating a Factor/Binary Variable on a data set.

Apply a Random Forest model and evaluate its results.

Clock2 Hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 1-hour long project-based course, you will learn how to (complete a training and test set using an R function, practice looking at data distribution using R and ggplot2, Apply a Random Forest model to the data, and examine the results using RMSE and a Confusion Matrix). Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Random ForestData ScienceData AnalysisMachine Learning

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. The Learner will get practice sampling a larger data set in R.

  2. The Learners will get practice doing creating a Categorical Variable in R.

  3. The Learner will get experience creating Testing and Training Data Sets.

  4. The Learner will get experience with the syntax of the Caret, an R package

  5. The Learner will evaluate the models accuracy using a Confusion Matrix.

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.