Dimensionality Reduction Techniques ML Frameworks

Implementations and tutorials of linear and non-linear dimensionality reduction algorithms (PCA, LDA, SVD, autoencoders, etc.) applied to datasets and images. Does NOT include general feature engineering, feature selection, or domain-specific applications that merely use dimensionality reduction as a preprocessing step.

There are 24 dimensionality reduction techniques frameworks tracked. 1 score above 50 (established tier). The highest-rated is beringresearch/ivis at 58/100 with 343 stars.

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#	Framework	Score	Tier	Stars	Language
1	beringresearch/ivis Dimensionality reduction in very large datasets using Siamese Networks	58	Established	343	Python
2	SENATOROVAI/singular-value-decomposition-svd-solver-course Singular Value Decomposition (SVD) is a fundamental linear algebra technique...	49	Emerging	16	Python
3	HayesYu/Spatiotemporal-Data-Analysis Data‑driven analysis of a large spatio‑temporal vector field dataset using...	36	Emerging	3	Jupyter Notebook
4	Labo-Lacourse/stepmix A Python package following the scikit-learn API for model-based clustering...	35	Emerging	83	Python
5	SundareshSankaran/nominal-dimension-reduction The Nominal Dimensionality Reduction repository provides a SAS Studio Custom...	32	Emerging	1	SAS
6	saniikakulkarni/Gaussian-Mixture-Model-from-scratch Implementing Gaussian Mixture Model from scratch using python class and...	30	Emerging	12	Jupyter Notebook
7	Ayoub-etoullali/SVD-Singular-Value-Decomposition This project demonstrates the application of Singular Value Decomposition...	25	Experimental	6	Jupyter Notebook
8	AsadiAhmad/PCA Dimension Reduction with PCA	23	Experimental	29	Jupyter Notebook
9	AsadiAhmad/LDA Dimension Reduction with LDA	23	Experimental	31	Jupyter Notebook
10	AsadiAhmad/Image-Classification-LDA-and-PCA Image Classification with Perceptron and LDA and PCA dimension reduction	23	Experimental	30	Jupyter Notebook
11	khairsahil/Image-Compression-Analysis An interactive Flask web app for image compression using PCA, SVD, and ICA,...	22	Experimental	—	Python
12	stabgan/Kernel-PCA We used Kernel PCA in this non linear dataset using both Python and R	22	Experimental	—	Python
13	cagatayuresin/interactive-pca 🔬 Interactive PCA Analysis Tool - Upload any CSV file and explore Principal...	22	Experimental	3	JavaScript
14	cl0reto/image-dimensionality-reduction Convert RGB images to grayscale and binary formats using Python. Simple, no...	22	Experimental	—	Jupyter Notebook
15	orhunyildiz/boyut-indirgeme-dimensionality-reduction Sınıflandırma problemleri için meta-sezgisel boyut azaltma aracının tasarımı...	20	Experimental	6	MATLAB
16	guilherme-hermano/PCA-FUNDAMENTALS Estudo prático dos fundamentos do PCA aplicado a dados tabulares (Wine...	19	Experimental	—	Jupyter Notebook
17	Saulorj/data_dimensionality_reduction Features reduction study using machine learn algorithm	17	Experimental	1	Jupyter Notebook
18	tamlablinz/RAVE_PCA Interactive Performance, Analysis and Visualization of RAVE Latent Spaces...	15	Experimental	13	Python
19	teddyoweh/Dimensionality-Reduction-PCA Dimensionality reduction is basically a process of reducing the amount of...	13	Experimental	11	Jupyter Notebook
20	Qaswara98/Thesis_PCA_vs_AE This project is a comparative study of Autoencoder (AE) and Principal...	13	Experimental	—	Jupyter Notebook
21	harjeet-blue/Dimensionality-Reduction-algos Applying Dimensionality Reduction algorithms i.e PCA, LDA, FDA on CIFAR-10,...	12	Experimental	6	Jupyter Notebook
22	dusansimic/DimensionalityReductionTechniques.jl Dimensionality reduction techniques for numerical matrices in Julia	11	Experimental	—	Julia
23	avadro112/Sklearn-PCA General analysis of dimensions using SciKit-Learn library included methods -...	11	Experimental	—	Python
24	KauaHenSilva/python_image_dimensionality_reduction This repository contains a Deep Learning project using Autoencoders for...	10	Experimental	2	Jupyter Notebook