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  • pdf文档 Learning Laravel

    0 码力 | 216 页 | 1.58 MB | 1 年前
    3

  • pdf文档 Back to Basics: Debugging Techniques

    Back to Basics: Debugging Techniques Bob Steagall CppCon 2021CppCon 2021 – Back to Basics: Debugging Techniques Copyright © 2021 Bob Steagall The Cost of Software Failures • January 2018, Tricentis’ salary -- $1.2T enterprise value lost for shareholders 2CppCon 2021 – Back to Basics: Debugging Techniques Copyright © 2021 Bob Steagall The Cost of Software Failures • Radiation overdoses from Therac-25 737 MAX MCAS system • System component design flaws 3CppCon 2021 – Back to Basics: Debugging Techniques Copyright © 2021 Bob Steagall Agenda • What are bugs? • What is debugging? • Challenges when
    0 码力 | 44 页 | 470.68 KB | 6 月前
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  • pdf文档 Solving Nim by the Use of Machine Learning

    Solving Nim by the Use of Machine Learning Exploring How Well Nim Can be Played by a Computer Mikael Nielsen Røykenes Thesis submitted for the degree of Master in Informatics: Programming and Networks the Use of Machine Learning Exploring How Well Nim Can be Played by a Computer Mikael Nielsen Røykenes c⃝ 2019 Mikael Nielsen Røykenes Solving Nim by the Use of Machine Learning http://www.duo.uio 3.4 The Sprague-Grundy Theorem . . . . . . . . . . . . . . . . . . . 6 4 Machine Learning 6 4.1 Reinforcement learning . . . . . . . . . . . . . . . . . . . . . . . . 7 4.1.1 The Principle . . . . .
    0 码力 | 109 页 | 6.58 MB | 1 年前
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  • pdf文档 Get off my thread: Techniques for moving k to background threads

    my thread: Techniques for moving work to background threads Anthony Williams Just Software Solutions Ltd https://www.justsoftwaresolutions.co.uk September 2020Get off my thread: Techniques for moving
    0 码力 | 90 页 | 6.97 MB | 6 月前
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  • ppt文档 Learning by Contributing to Rust Compiler - 陈于康

    第三届中国 Rust 开发者大会 Learning by Contributing to Rust Compiler Yukang github.com/chenyukang Engineer @ Cryptape Leveling Up in Rust • 2011 ~ 2014 EDA startup C/C++ • 2014 ~ 2020 DJI the best team What I’ve learned • Stay curious, learn by doing • You don't need to master Rust; learning Rust by hacking Rust compiler is a great way • Treat it as a game, have fun, remain patient
    0 码力 | 23 页 | 3.28 MB | 1 年前
    3

  • pdf文档 Techniques to Optimise Multi-threaded Data Building During Game Development

    1 Dominik Grabiec - Techniques to Optimise Multi-threaded Data Building During Game Development - CppCon 2024Hello My name is Dominik Grabiec This talk is Focusing on optimising the process around Background • What is data building? • Differences from Game Code • Assumptions and Concepts 2. <mark>Techniques</mark> • Keep Threads Busy • 3D Caching • Optimise Sorting • Avoid Blocking Threads 3. Questions 2Three Background What data building is Differences from normal game code Concepts used in presentation <mark>Techniques</mark> I've used to optimise the data building system Time for questions at end Numbers at bottom of</div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 99 页 | 2.40 MB <span class="hidden-xs-only" data-v-2d813be8>| 6 月前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"><!----></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/7e4056c13d45f2b7" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/pdf_24.png" alt="pdf文档" data-v-2d813be8> <span data-v-2d813be8>8 4 Deep <mark>Learning</mark> with Python 费良宏</span></a></h3> <div class="doc-desc" data-v-2d813be8> 文的自动分类 半监督学习 - 介于监督学习和无监督学习之间，算法: Graph Inference 或者Laplacian SVM 强化学习- 通过观察来学习做成如何的动作, 算法：Q-<mark>Learning</mark>以及时间差学习 机器学习－ 方法及流程 输入特征选择 – 基于什么进行预测 目标 – 预测什么 预测功能 – 回归、聚类、降维... Xn -> F(xn) -> T(x) 机器学习－ (NYU,2002), Facebook AI, Google Deepmind Theano (University of Montreal, ~2010), 学院派 Kersa, “Deep <mark>Learning</mark> library for Theano and TensorFlow” Caffe (Berkeley)，卷积神经网络,贾扬清 TensorFlow (Google) Spark MLLib </div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 49 页 | 9.06 MB <span class="hidden-xs-only" data-v-2d813be8>| 1 年前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"><!----></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/2881b245044b4577" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/pdf_24.png" alt="pdf文档" data-v-2d813be8> <span data-v-2d813be8>Leveraging the Power of C++ for Efficient Machine <mark>Learning</mark> on Embedded Devices</span></a></h3> <div class="doc-desc" data-v-2d813be8>Leveraging the power of C++ for efficient machine <mark>learning</mark> on embedded devices Adrian Stanciu adrian.stanciu.pub@gmail.com CppCon, 2023 1 / 50About me ◮ I am a software engineer from Romania ◮ I have Image classification ◮ Hand gesture recognition ◮ Summary ◮ Q&A 4 / 50Motivation 5 / 50Machine <mark>Learning</mark> (ML) ◮ Subfield of Artificial Inteligence (AI) ◮ Enables computers to learn from data and then consumption ◮ May have real-time performance constraints 7 / 50Machine <mark>learning</mark> on embedded devices ◮ Alternative to cloud-based machine <mark>learning</mark> ◮ Advantages: ◮ Real-time processing ◮ Low latency ◮ Reduced bandwidth</div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 51 页 | 1.78 MB <span class="hidden-xs-only" data-v-2d813be8>| 6 月前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"><!----></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/3fd19c22425f718b" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/pdf_24.png" alt="pdf文档" data-v-2d813be8> <span data-v-2d813be8>micrograd++: A 500 line C++ Machine <mark>Learning</mark> Library</span></a></h3> <div class="doc-desc" data-v-2d813be8>micrograd++: A 500 line C++ Machine <mark>Learning</mark> Library Gautam Sharma Independent Researcher gautamsharma2813@gmail.com Abstract—micrograd++ is a pure C++ machine <mark>learning</mark> li- brary inspired by Andrej Karpathy’s for building and training machine <mark>learning</mark> models. By leveraging the performance efficiency of C++, micro- grad++ offers a robust solution for integrating machine <mark>learning</mark> capabilities directly into C++-based Traditionally, all machine <mark>learning</mark> libraries are extremely bulky and very hard to integrate as third party dependencies. This aspect scares practitioners to adopt a C++ based machine <mark>learning</mark> library for prototyping</div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 3 页 | 1.73 MB <span class="hidden-xs-only" data-v-2d813be8>| 6 月前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#F7BA2A;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"><!----></i></span><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" style="color:#EFF2F7;"><!----></i></span><span class="el-rate__text" style="color:#ff9900;">3</span></div></div></li><li data-v-2d813be8><h3 class="doc-title" data-v-2d813be8><a href="/document/1b7a7ab8bf29582e" target="_blank" class="el-link el-link--primary" data-v-2d813be8><img src="/static/images/pdf_24.png" alt="pdf文档" data-v-2d813be8> <span data-v-2d813be8>When Lock-Free Still Isn't Enough: An Introduction to Wait-Free Programming and Concurrency <mark>Techniques</mark></span></a></h3> <div class="doc-desc" data-v-2d813be8></div> <div class="doc-info" data-v-2d813be8><span data-v-2d813be8>0 码力 | 33 页 | 817.96 KB <span class="hidden-xs-only" data-v-2d813be8>| 6 月前</span></span> <div role="slider" aria-valuenow="3" aria-valuetext="3" aria-valuemin="0" aria-valuemax="5" tabindex="0" class="el-rate float-right" data-v-2d813be8><span class="el-rate__item" style="cursor:auto;"><i class="el-rate__icon el-icon-star-on" 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",401,790,"NativeScript","NativeScript是一个开源框架，它允许开发人员使用JavaScript或TypeScript以及XML和CSS来构建跨平台本地移动应用程序，无需学习每个平台的特定语言或工具，同时提供与原生API的深度集成，实现高性能和优质的用户体验。",407,402,469,"Svelte","Svelte是一种现代的JavaScript框架，通过在构建时将代码转换为高效的原生JavaScript，实现在客户端以更少的运行时负担创建响应式、快速且轻量级的Web应用。",404,"Vue.js",406,"前端测试",470,"构建工具","后端开发",2479,"\u002F\u002Fwenku.it\u002Fuploads\u002Ff\u002F0\u002Fb\u002F8\u002Fa\u002Ff0b8aacdb939e3a464cb3568d136b744.jpeg","\u002F\u002Fwenku.it\u002Fuploads\u002F7\u002Ff\u002Ff\u002Ff\u002F8\u002F7fff8eee8d7d3c729ac86eee0a87062f.png","后端开发是指在构建网站或应用时负责处理服务器端逻辑、数据库管理和与前端交互的程序员工作领域。",441,".Net",440,802,"Conan","Conan 是一个开源的、去中心化的 C\u002FC++ 包管理器，它在所有平台和所有构建系统及编译器中都能工作。\n",443,"Crystal 是一种性能卓越的静态类型编程语言，它结合了Ruby的语法优雅和C语言的执行效率，适用于构建高效且易于维护的软件应用。",442,"C语言","C语言是一种通用、过程式的计算机编程语言，支持结构化编程、词汇变量作用域和递归等功能，是众多编程语言的基础，广泛应用于系统软件和应用软件的开发。",445,"Deno是由Node.js的创始人Ryan Dahl开发的一款现代的、安全的JavaScript和TypeScript运行时，具有内置的依赖管理和更强调安全性的特点。",792,"ffmpeg",396,151,"Go语言（Golang）是一门由Google开发的开源编程语言，以简洁、高效、并发支持和内置垃圾回收等特性而闻名，适用于构建可靠、高性能的软件应用。",418,"GraphQL",455,"Idris","Idris是一种函数式编程语言，它支持类型推断和强类型系统，特别强调可证明的正确性。","Java是一种通用的、跨平台的、面向对象的编程语言，广泛应用于企业级开发、移动应用开发、网络编程和大数据处理等领域。",791,"Apache ActiveMQ是Apache软件基金会所研发的开放源码消息中间件；由于ActiveMQ是一个纯Java程序，因此只需要操作系统支持Java虚拟机，ActiveMQ便可执行。",806,"Apache Unomi","Apache Unomi™（发音为“You know me”）是一个Java开源客户数据平台，一个旨在管理客户、潜在客户和访客数据的Java服务器，并帮助个性化客户体验，同时还提供尊重访客隐私规则（如GDPR）的功能。\n\n",788,"Apacke Wicket","Apache Wicket是一个基于Java的开源、面向对象的Web应用程序框架，它强调视图与业务逻辑的分离，提供组件化的开发模型，使得Web应用程序的开发更加简单、快速和可维护。","Spring",319,"Julia是一种高性能、通用、动态编程语言，特别适用于科学计算、数据分析和高性能计算领域。",398,"Kotlin",15,"Kotlin是一种由JetBrains开发的静态编程语言，旨在提供更简洁、更安全的代码，与Java完全互操作，并已成为Android官方支持的开发语言之一。",508,"Lean","Lean 是一种强大且灵活的函数式编程语言，它以简洁的语法、严格的类型检查和高效的编译器为特点，特别适用于形式化验证和定理证明等领域。",505,"Makefile","Makefile是一个工程化的编译方法，它通过一个文本文件来描述源文件之间的依赖关系以及编译和链接的规则，使得编译工作可以自动化进行。",37,"Nim 是一种静态类型的、编译型、系统编程语言，它结合了 Python、Ada 和 Modula 等成熟语言的成功概念。\n","Node.js 是一个基于 Chrome V8 引擎的 JavaScript 运行环境，允许开发者在服务器端运行 JavaScript，构建高效、可扩展的网络应用。",415,"Express.js","Express.js 是一个基于 Node.js 平台的轻量级、快速、无开销的 Web 应用开发框架，用于构建 Web 服务器和 API。",513,"Pascal","Pascal是一种过程式编程语言，具有结构化、强类型等特点，适用于教学和学术领域，以及编写应用程序和系统软件。","PHP 是一种创建动态交互性站点的强有力的服务器端脚本语言，广泛用于 Web 开发以生成动态网页内容。",448,"CakePHP","CakePHP是一个快速、安全的PHP框架，用于构建高效、可靠且易于维护的Web应用程序。",486,"Falcon","Falcon是一个高效、轻量级的PHP框架，它提供了一整套开发Web应用程序所需的工具和功能，帮助开发者快速构建稳定、可扩展的应用程序。","Laravel 是一个由Taylor Otwell所建立，自由开源的 PHP Web 框架，旨在实现的Web软件的MVC架构，并作为CodeIgniter的替代方案。","Python 是一种解释型、高级编程、通用编程语言，以简洁易读、功能强大、应用广泛和拥有丰富库支持而著称。",783,"Celery是一个简单、灵活且可靠的分布式任务队列，用于处理大量消息和异步任务调度，支持在多个机器、进程或线程上执行任务，并提供了丰富的异常处理和结果存储功能。\n\n",809,"Conda",95,"Django是一个高级的Python Web框架，它快速、安全且易于维护，适用于各种Web应用程序的开发。",412,"Flask是一个基于Python的轻量级Web应用框架，它简单易用，功能强大，支持扩展，适合快速构建Web服务和RESTful API。","Jupyter","Jupyter是一个开源的交互式Web应用程序，支持运行多种编程语言，让用户能够创建和共享包含实时代码、方程、可视化和文本的文档，广泛应用于数据科学、机器学习和数据分析等领域。",798,"ORM","ORM 就是通过实例对象的语法，完成关系型数据库的操作的技术，是\"对象-关系映射\"（Object\u002FRelational Mapping） 的缩写",786,"PyMuPDF","PyMuPDF是一个用于处理PDF文件的强大Python库，它提供了丰富的功能来解析、操作和生成PDF文档，包括数据提取、文本分析、图像处理等，且支持跨平台使用。",498,"PyWebIO",86,"PyWebIO 提供了一系列命令式的交互函数来在浏览器上获取用户输入和进行输出，将浏览器变成了一个“富\n文本终端”，可以用于构建简单的 Web 应用或基于浏览器的 GUI 应用。使用 PyWebIO，开发者能像编写终端脚本一样 (基于 input 和 print 进行交互) 来编写应用，无需具备 HTML 和 JS 的相关知识；PyWebIO 还可以方便地整合进现有的 Web 服务。非常适合快速构建对 UI 要求不高的应用。\n","Scrapy","Scrapy是一个用于网络爬取的快速、高级的Python框架，能够方便地从网站上抓取结构化数据。",487,"Tornado","Tornado是一个用Python编写的轻量级Web服务器和Web应用框架，它采用异步非阻塞IO的处理方式，具有出色的抗负载能力和优异的性能，旨在解决C10K问题，即处理大于或等于一万的并发连接。",485,"RISC-V","RISC-V是一个基于精简指令集原则的开源指令集架构，简易解释为与开源软件运动相对应的一种“开源硬件”。","Ruby 是一种优雅的、面向对象的、简洁易学的动态编程语言，以其高效的开发效率和独特的元编程功能而广受欢迎。",413,"Rails","Ruby on Rails（简称 Rails）是一个基于 Ruby 语言的 Web 应用开发框架，以其简洁、优雅和高效的开发方式，帮助开发者快速构建复杂的 Web 应用程序。",79,"Rust是一种高效、安全且并发的系统编程语言，特别适用于构建高性能、低开销的软件，包括操作系统、网络应用、嵌入式设备等。",397,477,"UML",98,"UML是一种广泛使用的软件建模语言，全称是Unified Modeling Language，是面向对象开发中一种通用的图形化建模语言。它综合了面向对象的建模语言、方法和过程，为软件开发的所有阶段提供模型化和可视化支持。",447,"其它语言",491,"区块链是一种分布式数据库技术，它允许网络中的参与者在不需要中心化信任机构的情况下进行安全、可追溯、不可篡改的数据交换和传输。",467,"开发测试",417,"微服务","微服务是一种将大型复杂应用程序拆分成多个小型、独立、可单独部署和扩展的服务的方法，每个服务都运行在自己的进程中，并使用轻量级通信机制进行通信。",785,"敏捷开发","敏捷开发是一种以人为核心、迭代、循序渐进的开发方法，它强调在快速变化的需求中通过高度的协作和灵活的响应来交付高质量的软件。",784,"架构设计",52,"架构设计是指在软件或计算机系统的开发过程中，对系统进行整体的规划和设计，以满足特定需求和功能，并关注系统中各个组件之间的相互关系和交互方式，以降低系统的复杂性，提高系统的可理解性和可维护性。",481,"汇编语言","汇编语言是一种低级编程语言，它使用助记符（mnemonics）来代替机器语言中的二进制代码，使得程序员能够更容易地编写、理解和修改计算机程序。",434,"\u002F\u002Fwenku.it\u002Fuploads\u002Fe\u002F0\u002Fc\u002Fe\u002F9\u002Fe0ce9096954e23a1a28197002e989b5f.jpg","\u002F\u002Fwenku.it\u002Fuploads\u002F7\u002Ff\u002F2\u002Fb\u002F9\u002F7f2b927210effe33346b9c827311e854.png","数据库是一种结构化组织和存储数据的系统，可方便地进行数据管理、检索和更新，提供有效的数据存储和访问机制。",506,"Apache Doris","Apache Doris是一个基于MPP架构的高性能实时分析数据库，以其亚秒级响应时间和支持超大数据集的能力，为实时数据分析提供了强大支持。",497,"Apache HBase","Apache HBase是一个开源的、分布式的、可扩展的、大数据存储系统，它利用Hadoop的HDFS作为其文件存储系统，并提供了类似于Google Bigtable的列式存储、高可靠性以及实时读写的能力。",429,"Apache Cassandra是一套开源分布式NoSQL数据库系统。它最初由Meta开发，用于改善电子邮件系统的搜索性能的简单格式数据，集Google BigTable的数据模型与Amazon Dynamo的完全分布式架构于一身。",789,"ClickHouse是Yandex开源的一个高性能列式数据库管理系统，专为在线分析处理（OLAP）设计，能够使用SQL进行实时数据分析并生成报告。",430,"Firebase",446,"Firebird是一个开源的关系型数据库管理系统（RDBMS），具有高性能、轻量级和跨平台特性，适用于各种应用开发场景。",494,"Greenplum",43,"Greenplum数据库是一个基于PostgreSQL的分布式数据仓库，采用MPP架构，提供强大的并行计算能力和海量数据管理能力，适用于大数据分析和数据科学应用。",427,"MongoDB是一个高性能、开源的、无模式的文档型数据库，使用类似于JSON的BSON格式存储数据，提供灵活的数据结构和水平扩展能力。",425,"MySQL是一个开源的关系型数据库管理系统（RDBMS），现属于Oracle旗下，因其高性能、易用性和可靠性而广泛应用于各种数据存储和管理需求中。",800,"PieCloudDB","PieCloudDB是杭州拓数派科技发展有限公司（OpenPie）推出的云原生虚拟数仓数据库产品，它以云原生技术重构数据存储和计算，实现数据的高效管理、安全加密和弹性伸缩，支持AI和数据科学，为企业用户提供强大的数据计算基础设施。\n",426,"PostgreSQL是一个开源的关系型数据库管理系统，具有强大的扩展性和支持复杂数据类型的特点。",428,"Redis是一个开源的高性能内存数据库，以键值对存储数据，并支持丰富的数据结构和高级缓存功能。",468,501,"SQLite是一款轻量级的关系型数据库管理系统，它不需要独立的服务器进程或操作系统支持，直接读写磁盘上的数据库文件，适用于嵌入式系统和移动应用。",492,"TiDB 是一个开源的分布式关系型数据库，兼容 MySQL 协议，设计目标是为云而生，提供高性能、水平扩展、高可用、易运维的分布式数据库解决方案。",499,"Vitess","Vitess是一个用于部署、扩展和管理大型MySQL实例集群的数据库解决方案。Vitess集MySQL数据库的很多重要特性和NoSQL数据库的可扩展性于一体。它的架构设计使得您可以像在物理机上一样在公共云或私有云架构中有效运行。它结合并扩展了许多重要的MySQL功能，同时兼具NoSQL数据库的可扩展性。 ","人大金仓(Kingbase)","Kingbase是一款面向大规模并发交易处理的企业级关系型数据库。 该产品支持严格的ACID特性、结合多核架构的极致性能、行业最高的安全标准，以及完备的高可用方案，并提供可覆盖迁移、开发及运维管理全使用周期的智能便捷工具。 产品融合了人大金仓在数据库领域几十年的产品研发和企业级应用经验，可满足各行业用户多种场景的数据处理需求。\n",451,34,"数据库中间件是位于应用程序和数据库管理系统之间的软件层，用于提供数据访问、连接管理和查询优化等功能，以简化数据库操作和提高系统性能。","数据库优化",77,"数据库工具是用于管理、开发、迁移、备份和恢复数据库的软件工具。",512,"DBeaver","DBeaver是一款免费且开源的多平台数据库管理工具，支持多种数据库并具备丰富的数据库管理功能。",511,"Navicat是一款功能强大的数据库管理工具，支持多种数据库系统，提供直观易用的界面，帮助用户轻松管理、开发和维护数据库，适用于数据库管理员、开发人员及中小企业等多种用户群体。",787,"phpMyAdmin","phpMyAdmin是一个基于Web的MySQL数据库管理工具，它提供了友好的图形界面，帮助用户轻松进行数据库的查询、创建、修改和删除等操作。",431,"数据库设计","系统运维",328,"\u002F\u002Fwenku.it\u002Fuploads\u002Fd\u002Fc\u002Fe\u002F7\u002F5\u002Fdce756afdfe873c14750c733e23fff73.jpg","\u002F\u002Fwenku.it\u002Fuploads\u002Fb\u002F6\u002Fd\u002F1\u002F3\u002Fb6d13efc4e52255c8384796b4b5cc861.png",419,424,"Darwin",465,36,808,"httpd",24,420,"Jenkins是一个开源的自动化服务器，用于自动执行软件构建、测试和部署任务。",145,"eBPF",31,"eBPF 是一项革命性的技术，起源于 Linux 内核，它可以在特权上下文中（如操作系统内核）运行沙盒程序。它用于安全有效地扩展内核的功能，而无需通过更改内核源代码或加载内核模块的方式来实现。",804,"Cilium 是一种用于网络、可观察性和安全性的云原生技术。它基于内核技术 eBPF，最初是为了更好的网络性能，现在针对不同的用例利用了许多附加功能。",483,461,"Prometheus是一款开源的监控和警报工具，用于收集和存储系统和服务的性能数据，并支持动态查询和告警规则配置。",423,482,"Traefik",421,476,29,"Zabbix 是一个开源的 IT 基础设施监控软件，用于监控各种网络服务、网络硬件、网络设备以及其他网络节点。",811,"存储",781,"网络与安全",815,"\u002F\u002Fwenku.it\u002Fuploads\u002Ff\u002F0\u002Fa\u002Fd\u002F2\u002Ff0ad2c0a9e46ee63f65bd12dadd14e12.jpeg",779,496,"Apache Flink","Apache Flink是一款高性能、通用的大数据处理引擎，用于进行实时数据流处理和批处理，具备精确一次的状态一致性语义和容错能力。",805,"Apache Karaf","Karaf是Apache旗下的一个开源项目。 Karaf同时也是一个基于OSGi的运行环境，Karaf提供了一个轻量级的OSGi容器，可以用于部署各种组件，应用程序。\n",495,"Apache Kyuubi","Apache Kyuubi 是一个为 Apache Spark 设计的多租户、高性能的 JDBC 网关服务，它提供了安全、可靠和高效的 Spark SQL 查询接入能力。",797,"Apache Ozone","Apache Ozone 是 Hadoop 的分布式对象存储系统，具有易扩展和冗余存储的特点。",462,"dapr",457,473,"Hadoop是一个用于处理大数据的分布式计算框架，它可以在大规模集群上存储和处理数据，并提供了可扩展、可靠和高容错性的数据存储和处理能力。",799,"Harbor 是一个开源的注册表，它通过策略和基于角色的访问控制来保护工件，确保镜像被扫描且无漏洞，并作为可信的签名。作为 CNCF 毕业项目，Harbor 提供了合规性、性能和互操作性，帮助您在 Kubernetes 和 Docker 等云原生计算平台上一致且安全地管理工件。\n\n",460,458,484,"OpenShift",75,"OpenShift是红帽公司（Red 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to Basics: Debugging \u003Cmark\u003ETechniques\u003C\u002Fmark\u003E\n\nBob Steagall\nCppCon 2021CppCon 2021 – Back to Basics: Debugging \u003Cmark\u003ETechniques\u003C\u002Fmark\u003E\nCopyright © 2021 Bob Steagall\n\nThe Cost of Software Failures\n\n• January 2018, Tricentis’ salary -- $1.2T enterprise value lost for shareholders\n\n2CppCon 2021 – Back to Basics: Debugging \u003Cmark\u003ETechniques\u003C\u002Fmark\u003E\nCopyright © 2021 Bob Steagall\n\nThe Cost of Software Failures\n\n• Radiation overdoses from Therac-25 737 MAX MCAS system\n\n• System component design flaws\n\n3CppCon 2021 – Back to Basics: Debugging \u003Cmark\u003ETechniques\u003C\u002Fmark\u003E\nCopyright © 2021 Bob Steagall\n\nAgenda\n\n• What are bugs?\n\n• What is debugging?\n\n• Challenges when","Solving Nim by the Use of Machine \u003Cmark\u003ELearning\u003C\u002Fmark\u003E Exploring How Well Nim Can be Played by a Computer Mikael Nielsen Røykenes Thesis submitted for the degree of Master in Informatics: Programming and Networks the Use of Machine \u003Cmark\u003ELearning\u003C\u002Fmark\u003E Exploring How Well Nim Can be Played by a Computer Mikael Nielsen Røykenes c⃝ 2019 Mikael Nielsen Røykenes Solving Nim by the Use of Machine \u003Cmark\u003ELearning\u003C\u002Fmark\u003E http:\u002F\u002Fwww.duo.uio 3.4 The Sprague-Grundy Theorem . . . . . . . . . . . . . . . . . . . 6 4 Machine \u003Cmark\u003ELearning\u003C\u002Fmark\u003E 6 4.1 Reinforcement \u003Cmark\u003Elearning\u003C\u002Fmark\u003E . . . . . . . . . . . . . . . . . . . . . . . . 7 4.1.1 The Principle . . . . . ","my thread: \u003Cmark\u003ETechniques\u003C\u002Fmark\u003E for moving\nwork to background threads\n\nAnthony Williams\n\nJust Software Solutions Ltd\nhttps:\u002F\u002Fwww.justsoftwaresolutions.co.uk\n\nSeptember 2020Get off my thread: \u003Cmark\u003ETechniques\u003C\u002Fmark\u003E for moving",90,"第三届中国 Rust 开发者大会 \u003Cmark\u003ELearning\u003C\u002Fmark\u003E by Contributing to Rust Compiler Yukang github.com\u002Fchenyukang Engineer @ Cryptape Leveling Up in Rust • 2011 ~ 2014 EDA startup C\u002FC++ • 2014 ~ 2020 DJI the best team What I’ve learned • Stay curious, learn by doing • You don't need to master Rust; \u003Cmark\u003Elearning\u003C\u002Fmark\u003E Rust by hacking Rust compiler is a great way • Treat it as a game, have fun, remain patient ",".pptx","1\nDominik Grabiec - \u003Cmark\u003ETechniques\u003C\u002Fmark\u003E to Optimise Multi-threaded Data Building During Game Development - CppCon 2024Hello\n\nMy name is Dominik Grabiec\n\nThis talk is \u003CTITLE\u003E\nFocusing on optimising the process around Background\n• What is data building?\n• Differences from Game Code\n• Assumptions and Concepts\n2. \u003Cmark\u003ETechniques\u003C\u002Fmark\u003E\n• Keep Threads Busy\n• 3D Caching\n• Optimise Sorting\n• Avoid Blocking Threads\n3. Questions\n\n2Three Background\nWhat data building is\nDifferences from normal game code\nConcepts used in presentation\n\n\u003Cmark\u003ETechniques\u003C\u002Fmark\u003E I've used to optimise the data building system\n\nTime for questions at end\nNumbers at bottom of"," 文的自动分类 半监督学习 - 介于监督学习和无监督学习之间，算法: Graph Inference 或者Laplacian SVM 强化学习- 通过观察来学习做成如何的动作, 算法：Q-\u003Cmark\u003ELearning\u003C\u002Fmark\u003E以及时间差学习 机器学习－ 方法及流程 输入特征选择 – 基于什么进行预测 目标 – 预测什么 预测功能 – 回归、聚类、降维... Xn -\u003E F(xn) -\u003E T(x) 机器学习－ (NYU,2002), Facebook AI, Google Deepmind Theano (University of Montreal, ~2010), 学院派 Kersa, “Deep \u003Cmark\u003ELearning\u003C\u002Fmark\u003E library for Theano and TensorFlow” Caffe (Berkeley)，卷积神经网络,贾扬清 TensorFlow (Google) Spark MLLib ","Leveraging the power of C++ for efficient\nmachine \u003Cmark\u003Elearning\u003C\u002Fmark\u003E on embedded devices\n\nAdrian Stanciu\nadrian.stanciu.pub@gmail.com\n\nCppCon, 2023\n\n1 \u002F 50About me\n\n◮ I am a software engineer from Romania\n◮ I have Image classification\n◮ Hand gesture recognition\n◮ Summary\n◮ Q&A\n\n4 \u002F 50Motivation\n\n5 \u002F 50Machine \u003Cmark\u003ELearning\u003C\u002Fmark\u003E (ML)\n\n◮ Subfield of Artificial Inteligence (AI)\n◮ Enables computers to learn from data and then consumption\n◮ May have real-time performance constraints\n\n7 \u002F 50Machine \u003Cmark\u003Elearning\u003C\u002Fmark\u003E on embedded devices\n\n◮ Alternative to cloud-based machine \u003Cmark\u003Elearning\u003C\u002Fmark\u003E\n◮ Advantages:\n\n◮ Real-time processing\n◮ Low latency\n◮ Reduced bandwidth","micrograd++: A 500 line C++ Machine \u003Cmark\u003ELearning\u003C\u002Fmark\u003E\nLibrary\n\nGautam Sharma\nIndependent Researcher\ngautamsharma2813@gmail.com\n\nAbstract—micrograd++ is a pure C++ machine \u003Cmark\u003Elearning\u003C\u002Fmark\u003E li-\nbrary inspired by Andrej Karpathy’s for building and training machine \u003Cmark\u003Elearning\u003C\u002Fmark\u003E\nmodels. By leveraging the performance efficiency of C++, micro-\ngrad++ offers a robust solution for integrating machine \u003Cmark\u003Elearning\u003C\u002Fmark\u003E\ncapabilities directly into C++-based Traditionally, all machine \u003Cmark\u003Elearning\u003C\u002Fmark\u003E libraries are extremely\nbulky and very hard to integrate as third party dependencies.\nThis aspect scares practitioners to adopt a C++ based machine\n\u003Cmark\u003Elearning\u003C\u002Fmark\u003E library for prototyping",978,"v3.3.0-beta.70","zh-TW","英语","es","fr","ja","中文（繁体）",56,"书栈网","https:\u002F\u002Fwww.bookstack.cn",{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},{},"文曲猩AI助手","\u002Farticle\u002Fabout",1000,"\u002F","_blank","2024-01-10T03:42:26Z"));</script><script 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