greitzmann

@greitzmann

greitzmann no introduction.

Python
Java
C++
All Personal Contributions
Forks Pause/Closed

    greitzmann/Recurrent-Knowledge-Graph-Embedding

    This is for the knowledge graph embedding recommendation framework – RKGE

    greitzmann/MCRec_PyTorch

    greitzmann/MCRec

    Source code for KDD 2018 paper "Leverage Meta-path based Context for Top-N Recommendation with a Neural Co-Attention Model"

    greitzmann/AICIty-reID-2020

    :red_car: The 1st Place Submission to AICity Challenge 2020 re-id track (Baidu-UTS submission)

    greitzmann/COVID19-KBQA-DEMO

    COVID-2019 中文知识问答系统

    greitzmann/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。

    greitzmann/OpenLearning4DeepRecsys

    Some deep learning based recsys for open learning.

    greitzmann/Probabilistic-Matrix-Factorization

    Python Implementation of Probabilistic Matrix Factorization(PMF) Algorithm for building a recommendation system using MovieLens ml-100k | GroupLens dataset

    greitzmann/SparkML

    Spark ML with pyspark

    greitzmann/Itemcf

    ItemBased Collaborative Filtering in Apache Spark

    greitzmann/track_sequence_anomaly_detection

    由时间空间成对组成的轨迹序列,通过循环神经网络lstm,自编码器auto-encode,时空密度聚类st-dbscan做异常检测

    greitzmann/sentiment_analysis

    LSTM,TextCNN,fastText情感分析,模型用 tf_serving 和 flask 部署成web应用

    greitzmann/recsys_faiss

    一个基于 fasttext + faiss 的商品内容相关推荐实现,nginx+uwsgi+flask / gunicorn+uvicorn+fastapi 提供api查询接口,增加Spark实现 Ansj+Word2vec+LSH+Phoenix

    greitzmann/UserProfile

    基于用户行为的用户画像项目

    greitzmann/RCF

    Tensorflow implementation of RCF

    greitzmann/RippleNet-PyTorch

    A PyTorch implementation of RippleNet

    greitzmann/ECommerceRecommendSystem

    商品大数据实时推荐系统。前端:Vue + TypeScript + ElementUI,后端 Spring + Spark

    greitzmann/flink-commodity-recommendation-system

    :whale:基于 Flink 的商品实时推荐系统。当用户产生评分行为时,数据由 kafka 发送到 flink,根据用户历史评分行为进行实时和离线推荐。实时推荐包括:基于行为和实时热门,离线推荐包括:历史热门、历史优质商品和 itemcf 。

    greitzmann/SelfAttentive

    Implementation of A Structured Self-attentive Sentence Embedding

    greitzmann/self-attentive-emb-tf

    Simple Tensorflow Implementation of "A Structured Self-attentive Sentence Embedding" (ICLR 2017)

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