e-hu
My interests focus on AdTech / Computational Advertising, Machine Learning, Data Mining, Recommender System.
Tokyo, Japan
Pinned Repositories
Ad-papers
Papers on Computational Advertising
ai-edu
AI education materials for Chinese students, teachers and IT professionals.
Ai-learn
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理等热门领域
AI_Learning_Hub
AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics
algorithm
solution of leetcode/lintcode/
android_SmartCampus
智慧校园Android端
androidpn4WX-server
我的毕业设计《Android平台校园消息推送服务的设计与实现》,基于AndroidPN实现的即时通信系统,Android服务端部分。
arima
2.6.3 Arima Time Series Modeling
SQL-Recommendation-System
Easy to implement a Recommendation System using SQL
Time-SVD-Plus-Plus
e-hu's Repositories
e-hu/ai-edu
AI education materials for Chinese students, teachers and IT professionals.
e-hu/Ai-learn
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理等热门领域
e-hu/AI_Learning_Hub
AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics
e-hu/algorithm
solution of leetcode/lintcode/
e-hu/awesome-dataset-tools
🔧 A curated list of awesome dataset tools
e-hu/bst.github.io
e-hu/CMS
校园管理系统
e-hu/CTRmodel
CTR prediction model based on spark(LR, GBDT, DNN)
e-hu/d2l-zh
《动手学深度学习》,英文版即伯克利深度学习(STAT 157,2019春)教材。面向中文读者、能运行、可讨论。
e-hu/deep_learning_object_detection
A paper list of object detection using deep learning.
e-hu/DeepRec
Implementation of Deep Learning based Recommender Algorithms with Tensorflow.
e-hu/DeepRec-1
推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction
e-hu/Emergency-Response-Notes
应急响应实战笔记,一个安全工程师的自我修养。
e-hu/fingerprintjs
Modern & flexible browser fingerprinting library
e-hu/free-books
互联网上的免费书籍
e-hu/free-programming-books
:books: Freely available programming books
e-hu/interview_internal_reference
2019年最新总结,阿里,腾讯,百度,美团,头条等技术面试题目,以及答案,专家出题人分析汇总。
e-hu/key-book
《机器学习理论导引》(宝箱书)的证明、案例、概念补充与参考文献讲解。在线阅读地址:https://datawhalechina.github.io/key-book/
e-hu/machine-learning-interview-enlightener
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
e-hu/ml-road
Machine Learning Resources, Practice and Research
e-hu/MLQuestions
Machine Learning and Computer Vision Engineer - Technical Interview Questions
e-hu/most-frequent-technology-english-words
程序员工作中常见的英语词汇
e-hu/pumpkin-book
《机器学习》(西瓜书)公式推导解析,在线阅读地址:https://datawhalechina.github.io/pumpkin-book
e-hu/Reco-papers
Classic papers and resources on recommendation
e-hu/school-api
校园教务系统接口,正方教务系统 SDK for Python
e-hu/spark-libFM
An implement of Factorization Machines (LibFM)
e-hu/Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
e-hu/testmarkdown
e-hu/uap-python
Python implementation of ua-parser
e-hu/xlearn
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.