In a recent video, I covered Random Forests and Neural Nets as part of the Bootcamp. In the most recent video, I covered Gradient Boosting and XGBoost. You can find the video on YouTube and the slides on Both are again in German with code examples in Python. But below, you find the English version of the content, plus code examples in R for caret, xgboost and h2o.

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These are the slides from my workshop: Introduction to Machine Learning with R which I gave at the University of Heidelberg, Germany on June 28th 2018. The entire code accompanying the workshop can be found below the video. The workshop covered the basics of machine learning. With an example dataset I went through a standard machine learning workflow in R with the packages caret and h2o: reading in data exploratory data analysis missingness feature engineering training and test split model training with Random Forests, Gradient Boosting, Neural Nets, etc.

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Dr. Shirin Elsinghorst

Biologist turned Bioinformatician turned Data Scientist

Data Scientist

Münster, Germany