Dimension Reduction

Lecture Notes for Dimension Reduction.

• Introduction
• Principal Components Analysis
• Multidimensional Scaling
• Kernel PCA
• Autoencoders
• Manifolds
• Isomap
• Local Linear Embedding
• Laplacian Eigenmaps
• t-SNE
• Determining Dimension
• Evaluation

Tutorials for Dimension Reduction

• Tutorial 1 (Solutions)
• Tutorial 2 (Solutions)

Data for Dimension Reduction

• Data on Development Indices
• Variable Description Development Indices
• Smart Meter Data
• Images Data