## Visualizing decision tree boundaries

Visualizing the decision intersections for a 2D classification via decision trees.

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Visualizing the decision intersections for a 2D classification via decision trees.

A lesser-known, step-like function approximation method.

A classic example of using a (random) forest classifier to sort features.

Using sklearn GridSearch to optimize hyperparameters.

Using MFCC for speech recognition.

Detecting outliers in 2D via various ways.

Topic modeling with LDA.

Nearest neighbor regression with sklearn.

Feature selection as part of a pipeline.

Gaussian naive Bayes classification basics.