Lists (27)
Sort Name ascending (A-Z)
Add-ons
Aging
Algorithm
Artificial Intelligence
Bioinformatics
CompBio
Data Science
DataViz
Deep Learning
EMR
Hands-on Tutorial
HPC/Parallel Computing
Machine Learning
Missing_Impute
NeoVim/Vim
NLP
Paper_Code
Paths to AI
Python Lib
QuantFin
R tools
SAS
Spatial Analysis
Stats
Web Scraping
Zotero
必备品
Stars
add statistical significance annotations on seaborn plots. Further development of statannot, with bugfixes, new features, and a different API.
A growing collection of bioinformatics tutorials, project guides, tools, and articles I’ve developed to make bioinformatics more accessible.
⚡ TabPFN: Foundation Model for Tabular Data ⚡
A high performance implementation of HDBSCAN clustering.
Creating beautiful plots of data maps
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
Enhance Tesseract OCR output for scanned PDFs by applying Large Language Model (LLM) corrections.
Improving XGBoost survival analysis with embeddings and debiased estimators
This repository houses scripts for training genetic scores of omic traits in INTERVAL
Short (less than 2 hour) intro to RAG workshop exercises
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Parallelized Mutual Information based Feature Selection module.
open-source feature selection repository in python
《数学建模导论》教程,全网最全数学建模模型与算法教程系列,带你走进数学建模的大门!
This is a repo with links to everything you'd ever want to learn about data engineering
AI for Science 论文解读合集(持续更新ing),论文/数据集/教程下载:hyper.ai
A Python-based compendium of GPU-optimized aging clocks.
Hone computational biology skills by re-enacting Figure 1 of modern biology papers
In the evolving world of Large Language Models (LLMs), crafting effective prompts has become an essential skill. That's why I've created this collection, showcasing the most impactful prompts of th…
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Curated list of project-based tutorials
A frictionless, pipeable approach to dealing with summary statistics
Visualize and annotate genomic coverage with ggplot2
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Computational phenotype pipeline for i2b2 based on KESER and KOMAP algorithms.
A beautiful, simple, clean, and responsive Jekyll theme for academics