某熊周刊系列:一周推荐外文技术资料(3.1)归纳于某熊周刊:一周推荐外文技术资料是笔者每周浏览外文技术网站中时发现的不错的文章/项目/书籍/教程的集锦,可以关注笔者的专栏某熊的全栈之路及时获取更新。资讯来源包括但不限于MediumTwitterGoogle PlusRedditHacker NewsDZoneGithub Trending。另外,周刊中的技术知识框架图参照笔者的2016:我的编程知识体系结构。请自备梯子。

技术纵横

编程语言

编程基础

  • gdbgui: A modern, browser-based frontend to gdb (gnu debugger). Add breakpoints, view stack traces, and more in C, C++, Go, and Rust! Simply run gdbgui from the terminal and a new tab will open in your browser.

Web

服务端应用程序架构

数据科学与机器学习

  • Self-driving cars in the browser: The goal of this project was to create a fully self-learning agent, that would be able to control a car in a 2D bottom-down environment. Written solely in JavaScript.

  • Deep Reinforcement Learning: An Overview: We give an overview of recent exciting achievements of deep reinforcement learning (RL). We start with background of deep learning and reinforcement learning, as well as introduction of testbeds. Next we discuss Deep Q-Network (DQN) and its extensions, asynchronous methods, policy optimization, reward, and planning. After that, we talk about attention and memory, unsupervised learning, and learning to learn. Then we discuss various applications of RL, including games, in particular, AlphaGo, robotics, spoken dialogue systems (a.k.a. chatbot), machine translation, text sequence prediction, neural architecture design, personalized web services, healthcare, finance, and music generation. We mention topics/papers not reviewed yet. After listing a collection of RL resources, we close with discussions.

  • Deep Forest: Towards An Alternative to Deep Neural Networks: In this paper, we propose gcForest, a decision tree ensemble approach with performance highly competitive to deep neural networks. Discussion in Reddit and Hacker News.

  • NanoNets: NanoNets : How to use Deep Learning when you have Limited Data

基础架构

信息安全

移动开发

延伸阅读:


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