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GateXAIML
Machine Learning: Unsupervised
Chapter 1: Unsupervised Learning
Introduction
Applications
Types of Unsupervised Learning
Clustering Example
Dimensionality Reduction Example
Chapter 2: Clustering Algorithms
Introduction
Example: Customer Purchase Data
Types of Clustering
1. Hard Clustering
2. Soft Clustering
Types of Clustering Methods
1. Centroid-based Clustering (Partitioning Methods)
2. Density-based Clustering (Model-based Methods)
3. Connectivity-based Clustering (Hierarchical Clustering)
4. Distribution-based Clustering
5. Fuzzy Clustering
Partition-based Clustering
K-means Clustering
K-medoids Clustering
Hierarchical Clustering
Agglomerative (Bottom-Up) Approach
Single-Linkage Method
Complete/Multiple-Linkage Method
Divisive (Top-Down) Approach
Chapter 3: Dimensionality Reduction
Principal Component Analysis (PCA)
Introduction and Motivation
Visualization of PCA Projection
Mathematical Formulation
GateXAIML · ML Concept Notes
Machine Learning: Unsupervised Learning
Chapter 1
Unsupervised Learning
5 sections
Introduction, Types of Unsupervised Learning
Chapter 2
Clustering Algorithms
19 sections
Introduction, Types of Clustering, Types of Clustering Methods...
Chapter 3
Dimensionality Reduction
4 sections
Principal Component Analysis (PCA)