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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