Python implementation of robust principal component analysis

A Julia package for exponential family principal component analysis (E-PCA).

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Computation of training set (X^T * X) and (X^T * Y) in a cross-validation setting using the fast algorithms by Engstrøm (2024).

📊 Computation and processing of models' parameters

This repository contains the code and data for the recreation and enrichment of the gastric (GC) cancer single-cell RNA-seq (scRNA-seq) data analysis pipeline described in the "Comprehensive analysis of metastatic gastric cancer tumour cells using single‑cell RNA‑seq" by Wang B. et. al, using the raw counts matrix they provide.

An app that finds and compares statistically similar college football teams

This project explores the options term structure for the National Stock Exchange of India using PCA. By analysing the relationship between option prices and their maturities, we aim to uncover market expectations and risk assessments.

Machine Learning 2018 course work (Testate)

Here we have fully implemented a number of algorithms related to machine learning

Seurat meets tidyverse. The best of both worlds.

ML Code Challenges

A RTI library for creating and visualizing Reflectance Transformation Imaging

Validation RMSLE obtained: 0.21163 which is less than the RMSLE score (0.22909) that won the Kaggle Competition.

Tools to perform ancestry projection to a reference dataset within the calculator pipeline (pgsc_calc)

pyChemometrics - Objects for multivariate analysis of chemometric and metabonomic datasets

This project is the first step in machine learning, using K Means and Principal Component Analysis.

Comprehensive EOF analysis in Python with xarray: A versatile, multidimensional, and scalable tool for advanced climate data analysis

Classification and pre-processing images of particle collisions using Machine Learning.

Repository of the online supplements to "Textbook English: A Multi-Dimensional Approach" (Le Foll, 2024).