course outline-analystadda

Course Outline

Unsupervised learning in Python

  1. Need for dimensionality reduction
  2. Introduction to Principal Component Analysis (PCA)
  3. Difference between PCAs and Latent Factors
  4. Introduction to Factor Analysis
  5. Patterns in the data in the absence of a target
  6. Segmentation with Hierarchical Clustering and K-means
  7. The measure of goodness of clusters
  8. Limitations of K-means
  9. Introduction to density-based clustering (DBSCAN)

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