caoyulong Goto Github PK
Type: User
Type: User
基于用户行为的推荐算法大赛---第四名(临兵斗列)
2017“达观杯”个性化推荐算法挑战赛-rank6
SVD & BPR+MatrixFactorization using a movie rating dataset ; RNN+BPR+BPTT using taobao marketing dataset
Adversarial Learning, Matrix Factorization, Recommendation
啊哈自然语言处理包,提供包括分词、依存句法分析、自动摘要、语义相似度计算、LDA 主题预测、词云等服务。
An Attention-Based User Behavior Modeling Framework for Recommendation
黑龙江大学软件工程专业2013级毕业设计
A Back-Propagation Neural Networks. Using the MNIST dataset.
This my implementation of BPNN on Hadoop
CrossDomainReviewTextRecommendation, 基于评论文本的跨领域推荐, 评分预测问题
Code for our paper Convolutaional Matrix Factorization for Document Context-Aware Recommendation (RecSys 2016)
Experimental codes for paper "Outer Product-based Neural Collaborative Filtering".
达观杯个性化推荐算法挑战赛
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
毕业设计-主动学习推荐系统的实现
毕业设计《基于Web的图书推荐系统展示平台》
##阿里移动推荐算法竞赛 ###
随着移动云计算和边缘计算的快速发展,以及人工智能的广泛应用,产生了边缘智能(Edge Intelligence)的概念。深度神经网络(例如CNN)已被广泛应用于移动智能应用程序中,但是移动设备有限的存储和计算资源无法满足深度神经网络计算的需求。神经网络压缩与加速技术可以加速神经网络的计算,例如剪枝、量化、卷积核分解等。但是这些技术在实际应用非常复杂,并且可能导致模型精度的下降。在移动云计算或边缘计算中,任务卸载技术可以突破移动终端的资源限制,减轻移动设备的计算负载并提高任务处理效率。通过任务卸载技术优化深度神经网络成为边缘智能研究中的新方向。Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge这篇文章提出了协同推断的**,将深度神经网络进行分区,一部分层在移动端计算,而另一部分在云端计算。根据硬件平台、无线网络以及服务器负载等因素实现动态分区,降低时延以及能耗。本项目给出了边缘智能方面的相关论文,并且给出了一个Python语言实现的卷积神经网络协同推断实验平台。关键词:边缘智能(Edge Intelligence),计算卸载(Computing Offloading),CNN模型分区(CNN Partition),协同推断(Collaborative Inference),移动云计算(Mobile Cloud Computing)
网上人才招聘系统
聚类下的协同推荐优化
考试系统--毕业设计
阿里移动推荐算法新人赛源代码
building a recommendation system using graph search methodologies. We will be comparing these different approaches and closely observe the limitations of each.
Handwritten Recognition Based on BP Neural Network
Code for our ACM RecSys 2017 paper "Personalizing Session-based Recommendation with Hierarchical Recurrent Neural Networks"
🤒医院预约挂号系统(期末项目/毕业设计/推荐)
2018/2019/校招/春招/秋招/自然语言处理(NLP)/深度学习(Deep Learning)/机器学习(Machine Learning)/C/C++/Python/面试笔记
Jointly Modelling Aspects, Ratings and Sentiments for Movie Recommendation (JMARS)
K-Means clustering algorithm for Hadoop
前端用bootstrap框架搭建ui+ajax异步请求,后台用SSH+Quartz框架搭建的图书管理系统。
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.