Student Guide: R Machine Learning Course Setup

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Manual Package Installation

packages <- c("swirl", "caret", "ggplot2", "randomForest", "gbm", 
              "MASS", "ISLR", "xgboost", "forecast", "TTR", "quantmod")

install.packages(packages, dependencies = TRUE)

library(swirl)

Alternative: Using renv

if (!requireNamespace("renv", quietly = TRUE)) {
  install.packages("renv")
}

renv::restore()

Start course using swirl

Package Information:

The course uses these R packages:

• swirl - Interactive learning environment
• caret - Machine learning framework
• ggplot2 - Data visualization
• randomForest - Random forest algorithm
• gbm - Gradient boosting machines
• MASS - Statistical functions and datasets
• ISLR - Datasets for statistical learning
• xgboost - Extreme gradient boosting
• forecast - Time series forecasting
• TTR - Technical trading rules
• quantmod - Financial data and modeling

Course Content Overview:

• Random_Forest
• Boosting
• Model_Based_Prediction
• Combining_Predictors
• Unsupervised_Prediction
• Forecasting_Lesson

Need Help?

1. Read the error message carefully
2. Check if all packages are installed: installed.packages()
3. Try restarting R: Ctrl+Shift+F10 (RStudio)
4. Contact your instructor

License and Attribution

Educational content created by Adam Mytnik, AGH University of Science and Technology.

This educational material is provided for academic purposes. Students may use and modify the code for learning purposes.

Note: Some datasets used in lessons (ISLR, MASS) have their own licenses. Please respect the original package licenses when using the data.