Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.

📊 Computation and processing of models' parameters

Brings bulk and pseudobulk transcriptomics to the tidyverse

Randomized Matrix Decompositions using R

A collection of Poisson lognormal models for multivariate count data analysis

Fast truncated singular value decompositions

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

Covariance Matrix Estimation via Factor Models

Seurat meets tidyverse. The best of both worlds.

光伏短期功率预测大赛 代码

This is an initiative to help understand Statistical methods and Machine learning in a naive manner. You will find scripts, and theoretical contents required to clarify concepts, especially for bio-informatic students.

Workshop on tidytranscriptomics: Performing tidy transcriptomics analyses with tidybulk, tidyverse and tidyheatmap

Computation of Sparse Eigenvectors of a Matrix

Sparse Principal Component Analysis (SPCA) using Variable Projection

Version 2.1.0 released

R package for High dimensional data analysis and integration with O2PLS!

R codes for common Machine Learning Algorithms

Animated Visualizations of Popular Machine Learning Algorithms

PCA, Factor Analysis, CCA, Sparse Covariance Matrix Estimation, Imputation, Multiple Hypothesis Testing