Microstrong0305's Stars
labuladong/fucking-algorithm
刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.
youngyangyang04/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!🚀
OI-wiki/OI-wiki
:star2: Wiki of OI / ICPC for everyone. (某大型游戏线上攻略,内含炫酷算术魔法)
thunlp/GNNPapers
Must-read papers on graph neural networks (GNN)
xzhih/one-key-hidpi
Enable macOS HiDPI and have a native setting.
hongleizhang/RSPapers
A Curated List of Must-read Papers on Recommender System.
datawhalechina/fun-rec
推荐系统入门教程,在线阅读地址:https://datawhalechina.github.io/fun-rec/
awesome-vpn/awesome-vpn
VPN/proxy WIKI .Find the best VPN/proxy 免费的VPN 代理 账号 翻墙 科学上网 梯子 机场
thunlp/PLMpapers
Must-read Papers on pre-trained language models.
aksnzhy/xlearn
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
maciejkula/spotlight
Deep recommender models using PyTorch.
shenweichen/DeepMatch
A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.
wangshusen/RecommenderSystem
zhulei227/ML_Notes
机器学习算法的公式推导以及numpy实现
DA-southampton/Tech_Aarticle
主要是我是日常看过的不错的文章的资源汇总,方便自己也分享给大家。有些我看过的,就会做简单的解读,没看过的,就先罗列一下,然后之后看了把解读更新上;涉及到搜索/推荐/自然语言处理。
shenweichen/AlgoNotes
【浅梦学习笔记】文章汇总:包含 排序&CXR预估,召回匹配,用户画像&特征工程,推荐搜索综合 计算广告,大数据,图算法,NLP&CV,求职面试 等内容
Tencent/TurboTransformers
a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU.
LYuhang/GNN_Review
GNN综述阅读报告
SmallVagetable/machine_learning_python
通过阅读网上的资料代码,进行自我加工,努力实现常用的机器学习算法。实现算法有KNN、Kmeans、EM、Perceptron、决策树、逻辑回归、svm、adaboost、朴素贝叶斯
HongYiMU/TheAlgorithm
FeiSun/BERT4Rec
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
wangzhegeek/EGES
wayfair/pylift
Uplift modeling package.
DSXiangLi/CTR
CTR模型代码和学习笔记总结
peiss/ant-learn-recsys
推荐系统从入门到实战
tscheepers/word2vec
Python implementation of Word2Vec using skip-gram and negative sampling
nxs5899/Recommender-System-LightFM
scalable Recommeder System for e-commerece using LightFM package in python
TPLink32/logistic-regression
对逻辑回归各种用法的总结,包括线性,多类,并行,分布式,在线,优化方案
nzw0301/word2vec4j
tzcurtain/movielen_recommend_system
基于二分网络对movielens进行分类推荐预测