Wolfram U

Automated Structure Discovery: Unsupervised Learning

Estimated Time: 30 min

Course Level: Beginner


Wolfram Language has functions that work directly on many types of data and automatically extract some sort of structure from it. Built-in functions used for unsupervised learning tasks include FindClusters, ClusteringTree and ClusteringComponents. You can classify new samples according to the clusters present in the data using ClusterClassify. Other functions like FeatureExtract, FeatureNearest, FeatureSpacePlot and DimensionReduce provide tools for automatic exploration of the data in the feature space. This lesson demonstrates the use of these functions and helps you get started with unsupervised machine learning.

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You'll Learn To

  • Use built-in functions for unsupervised machine learning
  • Identify and visualize clusters in data
  • Classify data based on existing clusters
  • Explore data in the feature space