Interactive

In this interactive tutorial you will learn to understand hierarchical clustering. You can modify the number of points, but that won’t be our focus in this tutorial. Let’s use 12 points, just to have a different setup than in the 101 lecture. We will focus on the impact of the parameters “distance metric” and linkage …

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This dashboard teaches you why multiple trees outperform a single decision tree. The data is artificial. There is a diagonal line, separating two classes. All green points are part of class B and are to be found in the upper left triangle. All red points are part of class B and are to be found …

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This interactive dashboard will help you to understand train / validation / test splits.  You can modify the data count between 10 and 1000. As default I set 60 % training ratio. That leaves 40 % for validation and testing. With the second slider you can set validation ratio. Test ratio is set implicitly, because …

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This interactive dashboard helps you to understand univariate linear regression. You have some observations – represented by their x and y coordinates in the first plot, colored in blue. They are defined by a slope, an offset, and some noise. If you modify the parameters, you see the impact. You also see a model result, …

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Univariate Linear Regression Train / Validation / Test Split Receiver Operating Characteristics Curve Random Forests Hierarchical Clustering Upper Confidence Bound Understanding Convolutions Metropolis Hastings (simple 1D distribution) Metropolis Hastings (complex 1D distribution) Metrpolis Hastings (multivariate 2D distributions)