Michaelhuazhang's Stars
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
dennybritz/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
imarvinle/awesome-cs-books
🔥 经典编程书籍大全,涵盖:计算机系统与网络、系统架构、算法与数据结构、前端开发、后端开发、移动开发、数据库、测试、项目与团队、程序员职业修炼、求职面试等
UKPLab/sentence-transformers
State-of-the-Art Text Embeddings
jina-ai/clip-as-service
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
mrdbourke/pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
wandb/wandb
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
changgyhub/leetcode_101
LeetCode 101:力扣刷题指南
hongleizhang/RSPapers
RSTutorials: A Curated List of Must-read Papers on Recommender System.
RUCAIBox/RecBole
A unified, comprehensive and efficient recommendation library
yangjianxin1/GPT2-chitchat
GPT2 for Chinese chitchat/用于中文闲聊的GPT2模型(实现了DialoGPT的MMI**)
wangshusen/RecommenderSystem
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。
Tyson0314/java-books
程序员常读书单整理,附下载地址,希望对你有帮助。书单包括设计模式、计算机网络、操作系统、数据库、数据结构与算法、架构、中间件等等。本仓库持续更新中,可以star一下,下次找书直接在上面搜索
guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.
jc-LeeHub/Recommend-System-tf2.0
原理解析及代码实战,推荐算法也可以很简单 🔥 想要系统的学习推荐算法的小伙伴,欢迎 Star 或者 Fork 到自己仓库进行学习🚀 有任何疑问欢迎提 Issues,也可加文末的联系方式向我询问!
drabastomek/learningPySpark
Code base for the Learning PySpark book (in preparation)
mrdbourke/cs329s-ml-deployment-tutorial
Code and files to go along with CS329s machine learning model deployment tutorial.
RUCAIBox/CIKM2020-S3Rec
Code for CIKM2020 "S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization"
yuangh-x/2022-NIPS-Tenrec
LongxingTan/Data-competitions
My Data Competition Solutions
CRIPAC-DIG/Fi_GNN
[CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"
qinjr/UBR4CTR
UBR4CTR is the code for our proposed User Behavior Retrieval for CTR Prediction framework in SIGIR 2020.
MaurizioFD/recsys-challenge-2020-twitter
The complete code and notebooks used for the ACM Recommender Systems Challenge 2020 by our team BanaNeverAlone at Politecnico di Milano
wilsonlsm006/NLP_BERT_binary-classification
使用BERT模型用于二分类任务
Eleanoryuyuyu/RecommendRelative
推荐系统相关模型 包括召回和排序
recsysgroup/i2i_recall
heyunh2015/AttList
data and code of AttList from CIKM2019
sumitsidana/recsys_challenge_2020
This repository contains the code for 4th place solution for approach to RecSys Challenge 2020.
Lemonace/PIER_code