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Fengshenbang-LM(封神榜大模型)是IDEA研究院认知计算与自然语言研究中心主导的大模型开源体系，成为中文AIGC和认知智能的基础设施。
交易模块
DeepGEMM: clean and efficient FP8 GEMM kernels with fine-grained scaling
搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号）
面向北京码农同胞的从0开始的买房踩盘实录，目标只有一个: 每一分钱都花的明白(持续补充和完善ing…)
该仓库尝试整理推荐系统领域的一些经典算法模型
tensorflow实战练习，包括强化学习、推荐系统、nlp等
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommen…
CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)
Implementation of unified embedding model from Embedding-based Retrieval in Facebook Search.
Universal User Representation Pre-training for Cross-domain Recommendation and User Profiling
Best Practices on Recommendation Systems
Solution to the Debiasing Track of KDD CUP 2020
Graph Neural Network for Tag Ranking in Tag-enhanced Video Recommendation（CIKM20）
Simple wrapper of tabula-java: extract table from PDF into pandas DataFrame
Classic papers and resources on recommendation
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。