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
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 Forest
  • Data Science
  • Data Analysis
  • Machine 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.