Let’s move on to unsupervised part ! This cheatsheet covers the key concepts, illustrations, otpimisaton program and limitations for the most common types of algorithms. Don’t hesitate to drop a comment !

We’ll cover :

  • Principal Component Analysis (PCA)
  • Kernel PCA
  • Factor Analysis
  • K-Means
  • Gaussian Mixture Model (GMM)
  • Expectation Maximization (EM)
  • Hierarchical Clustering
  • Nearest Neighbor Chain
  • Density Based Spatial Clustering of Applications with noise (DBSCAN)
  • Non-negative Matrix Factorisation model (NMF)
  • Independent Component Analysis (ICA)

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