Unsupervised Learning

Unsupervised Learning discovers hidden patterns in data without pre-existing labels, allowing for automated pattern discovery and grouping.

Key Concepts

  • Clustering
  • Dimensionality Reduction
  • Association Rules

Best Practices

  • Data Preprocessing
  • Algorithm Selection
  • Cluster Validation

Example

# Clustering Example from sklearn.cluster import KMeans kmeans = KMeans(n_clusters=3) clusters = kmeans.fit_predict(X)

Important Considerations

Tools & Resources

Related Topics