Extensible, parallel implementations of t-SNE

Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.

scGEAToolbox: Matlab toolbox for single-cell gene expression analyses

Brings bulk and pseudobulk transcriptomics to the tidyverse

Detection, extraction, and cluster assignment of S. Infantis pESI

Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE

Results of a Data analytics project at TH Wildau. Created with Orange data analytics tool, Data source: https://www.kaggle.com/datasets/PromptCloudHQ/us-jobs-on-monstercom

Prediction of students' dropout using classification models. Data visualisation, feature selection, dimensionality reduction, model selection and interpretation, parameters tuning.

In this repository we perform Principal component analysis ( PCA ) on swiss dataset & t-distributed Stochastic Neighbor Embedding (t-sne) on optdigits dataset.

Case Summary Perform Principal component analysis and perform clustering using first 3 principal component scores (both Heirarchical and k mean clustering(scree plot or elbow curve) and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data (class column we have ignored at the begining…

Code for the AP project for the class 'Advanced Python for NLP' on Russian noun clustering.

Feasibility of a classification engine of articles into different predefined categories, with a sufficient level of precision, based on an image and a description.

PANDORA - Predictive Analytics aNd Data Oriented Research Applications 💻

This repository implements customer segmentation techniques to analyze credit card user behavior and identify distinct customer groups. By leveraging Python libraries like pandas, Scipy and scikit-learn.

Customer segmentation through their behavior, their habits and their personal data.

GPU Accelerated t-SNE for CUDA with Python bindings

R wrappers to connect Python dimensional reduction tools and single cell data objects (Seurat, SingleCellExperiment, etc...)

Create an unsupervised Machine Learning Model to determine actively traded cryptocurrencies for new investment.

Project that analyzes performance of clustering and dimensionality reduction techniques on 2 datasets