Unsupervised Learning

#machine-learning #interview

In unsupervised learning, the dataset is a collection of feature vectors and the model has to learn the density/distribution of the class probability. There is no target label. Most of the time unsupervised learning is used for finding patterns, commonalities or anomalies in the dataset without prior knowledge.

Examples of Unsupervised Learning

  • Dimensionality Reduction
  • Clustering
  • Outlier Detection
  • Customer Segmentation
  • Anomaly Detection

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