yu45020

yu45020's Stars

• ventoy/Ventoy

  A new bootable USB solution.

  Language:C63.2k6562.3k4.1k

• mattermost-community/focalboard

  Focalboard is an open source, self-hosted alternative to Trello, Notion, and Asana.

  Language:TypeScript22.1k1502.4k2k

• ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

  500 AI Machine learning Deep learning Computer vision NLP Projects with code

  20.7k604555.2k

• pavlobu/deskreen

  Deskreen turns any device with a web browser into a secondary screen for your computer. ⭐️ Star to support our work!

  Language:TypeScript17.6k249166963

• EpistasisLab/tpot

  A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

  Language:Python9.8k2889221.6k

• missing-semester-cn/missing-semester-cn.github.io

  the CS missing semester Chinese version

  Language:CSS6.3k3817993

• spantaleev/matrix-docker-ansible-deploy

  🐳 Matrix (An open network for secure, decentralized communication) server setup using Ansible and Docker

  Language:Jinja4.9k961.4k1k

• christophM/interpretable-ml-book

  Book about interpretable machine learning

  Language:Jupyter Notebook4.8k1392061.1k

• SFUMECJF/cmake-examples-Chinese

  快速入门CMake,通过例程学习语法。在线阅读地址：https://sfumecjf.github.io/cmake-examples-Chinese/

  Language:C++2.4k219356

• CoinCheung/pytorch-loss

  label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

  Language:Python2.2k2339373

• mlech26l/ncps

  PyTorch and TensorFlow implementation of NCP, LTC, and CfC wired neural models

  Language:Python2k7367321

• krasserm/bayesian-machine-learning

  Notebooks about Bayesian methods for machine learning

  Language:Jupyter Notebook1.8k7618463

• manujosephv/pytorch_tabular

  A standard framework for modelling Deep Learning Models for tabular data

  Language:Python1.4k21155140

• scottclowe/matlab-schemer

  Apply and save color schemes in MATLAB with ease.

  Language:MATLAB1.2k3034276

• lucidrains/tab-transformer-pytorch

  Implementation of TabTransformer, attention network for tabular data, in Pytorch

  Language:Python8161615103

• analyticalmindsltd/smote_variants

  A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features

  Language:Jupyter Notebook6381536138

• propublica/compas-analysis

  Data and analysis for 'Machine Bias'

  Language:Jupyter Notebook631480267

• d-li14/efficientnetv2.pytorch

  PyTorch implementation of EfficientNetV2 family

  Language:Python460111093

• eliocamp/ggnewscale

  Multiple Fill, Color and Other Scales in `ggplot2`

  Language:TeX407116718

• youyanggu/covid19_projections

  COVID-19 Projections Using Machine Learning

  369361588

• vballoli/nfnets-pytorch

  NFNets and Adaptive Gradient Clipping for SGD implemented in PyTorch. Find explanation at tourdeml.github.io/blog/

  Language:Python34382829

• LeeDoYup/RobustSTL

  Unofficial Implementation of RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019)

  Language:Jupyter Notebook28181651

• Yu-Group/covid19-severity-prediction

  Extensive and accessible COVID-19 data + forecasting for counties and hospitals. 📈

  Language:Jupyter Notebook228231492

• youyanggu/yyg-seir-simulator

  Underlying SEIR simulator for the YYG / covid19-projections.com model

  Language:Python20313561

• uzaymacar/comparatively-finetuning-bert

  Comparatively fine-tuning pretrained BERT models on downstream, text classification tasks with different architectural configurations in PyTorch.

  Language:Python1208128

• d-li14/regnet.pytorch

  PyTorch-style and human-readable RegNet with a spectrum of pre-trained models

  Language:Python686313

• TimoMatzen/RBM

  Restricted Boltzmann Machine in R

  Language:R29349

• stacklens/python-magic-method-cookbook

  介绍Python魔法方法的系列文章

  28207

• gruvw/latex-setup

  My setup for writing LaTeX documents

  23446

• jm4474/Courses-IntroEconometrics-Ph.D

  This course provides a graduate level introduction to probability and statistics. The course was designed for economists starting their doctoral education. Edits, comments, and suggestions are welcome.

  236017