Dimensionality-Reduction-Techniques

This project intends to show the ways we can perform dimensionality reduction techniques on our data.

Methods that are covered in the project:

1. Principal component analysis (PCA)
2. Non-negative matrix factorization (NMF)
3. Kernel PCA
4. Factor Analysis (FA)
5. Independent Component Analysis
6. Incremental principal components analysis (IPCA)
7. Mini-batch Sparse Principal Components Analysis
8. Sparse Principal Components Analysis (SparsePCA)
9. Truncated SVD
10. Linear Discriminant Analysis
11. t-SNE
12. UMAP