zxhymjcx Goto Github PK

alphafm

Multi-thread implementation of Factorization Machines with FTRL for binary-class classification problem.

angel

A Flexible and Powerful Parameter Server for large-scale machine learning

awesome-chatbot

Awesome Chatbot Projects,Corpus,Papers,Tutorials.Chinese Chatbot =>:

bert-bilstm-crf-ner

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

cppjieba

"结巴"中文分词的C++版本

deep-learning-for-recommendation-systems

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

deepqa

My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot

deeprec

Implementation of Deep Learning based Recommender Algorithms with Tensorflow.

elasticsearch-spark-recommender

Use Jupyter Notebooks to demonstrate how to build a Recommender with Apache Spark & Elasticsearch

flink

Apache Flink

from_coder_to_expert

2019年最新总结，从程序员到CTO，从专业走向卓越，分享大牛企业内部pdf与PPT

ftrl_proximal_lr

Multithreaded Asynchronous FTRL Proximal Implementation

grpc

The C based gRPC (C++, Python, Ruby, Objective-C, PHP, C#)

higuides

insuranceqa-corpus-zh

OpenData in insurance area for Machine Learning Tasks

jieba

结巴中文分词

lightctr

Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based machine learning, philosophy of Parameter Server and Ring-AllReduce collective communication.

lstm_sentiment

ml_cia

公众号机器学习荐货情报局所有代码

models

Models and examples built with TensorFlow

movie_recommend

基于Spark的电影推荐系统，包含爬虫项目、web网站、后台管理系统以及spark推荐系统

movie_recommender

MovieLens based recommender system.使用MovieLens数据集训练的电影推荐系统。

movierecommender

基于Mahout实现协同过滤推荐算法的电影推荐系统

mpvue-xbyjshop

前端mpvue🚀后端nodejs🔋+thinkjs+mysql📂微信小程序商城

neural_collaborative_filtering

Neural Collaborative Filtering

news-duplicated

文本去重算法，研究自推荐系统中新闻的去重，采用了雅虎的Near-duplicates and shingling算法，服务端用c实现，客户端用java实现，利用thrift框架进行通信，为了提高扩展性，去重可以在服务端实现，服务器也提供了计算的接口，方便客户端自己扩展

openbmc

OpenBMC Distribution

qa-retrieval-system

qa_lstm

readandlearn