谢赛's repositories
open_clip
An open source implementation of CLIP.
hello-algo
《Hello 算法》:动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新,English version ongoing
Qwen2
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud.
LongVA
Long Context Transfer from Language to Vision
d2l-zh
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
farfalle
🔍 AI search engine - self-host with local or cloud LLMs
fun-rec
推荐系统入门教程,在线阅读地址:https://datawhalechina.github.io/fun-rec/
llm_interview_note
主要记录大语言大模型(LLMs) 算法(应用)工程师相关的知识及面试题
AlphaTree-graphic-deep-neural-network
AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN),图神经网络(GNN),NLP,大数据相关的发展路书(roadmap), 并附海量源码(python,pytorch)带大家消化基本知识点,突破面试,完成从新手到合格工程师的跨越,其中深度学习相关论文附有tensorflow caffe官方源码,应用部分含推荐算法和知识图谱
QASystemOnMedicalKG
A tutorial and implement of disease centered Medical knowledge graph and qa system based on it。知识图谱构建,自动问答,基于kg的自动问答。以疾病为中心的一定规模医药领域知识图谱,并以该知识图谱完成自动问答与分析服务。
TakeHomeDataChallenges
My solution to the book <A collection of Data Science Take-home Challenges>
DirectAU
KDD'2022: Towards Representation Alignment and Uniformity in Collaborative Filtering
CROLoss
Code for paper CROLoss: Towards a Customizable Loss for Retrieval Models in Recommender Systems
AI_Tutorial
精华机器学习,NLP,图像识别, 深度学习等人工智能领域学习资料,搜索,推荐,广告系统架构及算法技术资料整理
cpp_new_features
2021年最新整理, C++ 学习资料,含C++ 11 / 14 / 17 / 20 / 23 新特性、入门教程、推荐书籍、优质文章、学习笔记、教学视频等
BARS
Towards open benchmarking for recommender systems https://openbenchmark.github.io/BARS
GraphSAGE
Representation learning on large graphs using stochastic graph convolutions.
AlgoNotes
公众号【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
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.
Recommender-System-with-TF2.0
Recurrence the recommender paper with Tensorflow2.0
dl_inference
通用深度学习推理服务,可在生产环境中快速上线由TensorFlow、PyTorch、Caffe框架训练出的深度学习模型。
daisyRec
A developing recommender system in pytorch. Algorithm: KNN, LFM, SLIM, NeuMF, FM, DeepFM, VAE and so on, which aims to fair comparison for recommender system benchmarks
guofei9987.github.io
个人博客,欢迎fork