YunJiao-Chen's repositories
tab-transformer-pytorch
Implementation of TabTransformer, attention network for tabular data, in Pytorch
auto-sklearn
Automated Machine Learning with scikit-learn
awesome-self-supervised-learning-for-tabular-data
A collection of research materials on SSL for tabular data
causalml
Uplift modeling and causal inference with machine learning algorithms
docker-handbook-projects
Project codes used in "The Docker Handbook"
DeepCTR-Torch
【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.
DeepIV
Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction
FLASH-pytorch
Implementation of the Transformer variant proposed in "Transformer Quality in Linear Time"
FuxiCTR
A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io/tutorials
leetcode-master
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
llama.cpp
Port of Facebook's LLaMA model in C/C++
LLMSurvey
The official GitHub page for the survey paper "A Survey of Large Language Models".
ml-stable-diffusion
Stable Diffusion with Core ML on Apple Silicon
mlc-llm
Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
MLOPs-Primer
A collection of resources to learn about MLOPs.
nlp_paper_study
研读顶会论文，复现论文相关代码
notebooks
Jupyter notebooks for the Natural Language Processing with Transformers book
pygta5
Explorations of Using Python to play Grand Theft Auto 5.
pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
pytorch-widedeep
A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
rank4_NLP_textclassification
阿里云天池零基础入门NLP比赛_rank4选手比赛总结: https://tianchi.aliyun.com/competition/entrance/531810/introduction
ResnetGPT
用Resnet101+GPT搭建一个玩王者荣耀的AI
Software-Engineering-at-Google
《Software Engineering at Google》的中文翻译版本
Stacking-Blending-Voting-Ensembles
This repository contains an example of each of the Ensemble Learning methods: Stacking, Blending, and Voting. The examples for Stacking and Blending were made from scratch, the example for Voting was using the scikit-learn utility.
tabular-dl-revisiting-models
(NeurIPS 2021) The official implementation of the paper "Revisiting Deep Learning Models for Tabular Data"
transtab
NeurIPS'22 | TransTab: Learning Transferable Tabular Transformers Across Tables
whisper.cpp
Port of OpenAI's Whisper model in C/C++
x-transformers
A simple but complete full-attention transformer with a set of promising experimental features from various papers