Google SRE 技术
包含SRE职责,如何处理运维事情,应急、监控、高并发高可用控制、以及Google的分布式架构、运维系统等。
2017-2018年机器学习顶会优质论文集合 包含ACL EMNLP AAAI等优质会议期刊上的推荐论文集 涉及自然语言处理、推荐系统、强化学习等领域
数据挖掘导论(完整版).Introduction.To.Data.Mi 带标签,带习题答案,两本数据挖掘书供学习参考
书中关键代码下载:https://github.com/guangxush/JavaAlgorithms
What Do We Understand About Convolutional Networks?论文 卷积神经网络(CNN)在计算机视觉领域已经取得了前所未有的巨大成功,但我们目前对其效果显著的原因还没有全面的理解。约克大学电气工程与计算机科学系的 Isma Hadji 和 Richard P. Wildes 发表了论文《What Do We Understand About Convolutional Networks?》,对卷积网络的技术基础、组成模块、当前现状和研究前景进行了梳理,介绍了我们当前对 CNN 的理解。
10篇经典的推荐系统文章,Reinforcement Learning based Recommender System using Biclustering Technique;Learning Continuous User Representations through Hybrid Filtering with doc2vec;Deep Reinforcement Learning for List-wise Recommendations;Leveraging Long and Short-term Information in Content-aware Movie Recommendation;Deep Collaborative Autoencoder for Recommender Systems: A Unified Framework for Explicit and Implicit Feedback;Use of Deep Learning in Modern Recommendation System: A Summary of Recent Works;A Context-Aware User-Item Representation Learning for Item Recommendation;Pixie: A System for Recommending 3+ Billion Items to 200+ Million Users in Real-Time;Recommender Systems with Random Walks: A Survey;Deep Learning Based Recommender System: a Survey and New Perspectives;Auto-Encoding User Ratings via Knowledge Graphs in Recommendation Scenarios;A Deep Multimodal Approach for Cold-start Music Recommendation
强化学习PPT An Introduction to RL - SuttonBook;Algorithms for RL