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2016年科技阅读列表

發布時間:2025/3/21 编程问答 23 豆豆
生活随笔 收集整理的這篇文章主要介紹了 2016年科技阅读列表 小編覺得挺不錯的,現在分享給大家,幫大家做個參考.


之前整理的2015年科技閱讀列表[600篇],有人覺得看不過來,我就把一些個人喜歡的重新列出來,再加到今年列表中,慢慢補充,加上分類標簽,歡迎大家留言翻譯。比如時間在幾周內,站內聯系。更新 2016/05/23

1. 技術架構

  • Everyday Algorithms: Elevator Allocation 電梯算法調度
  • Le Cloud Blog 系統設計系列 scalability入門
  • Airbnb Shares The Keys To Its Infrastructure Airbnb基礎架構 翻完
  • Backend infrastructure at Spotify Spotify架構
  • Jepsen: On the perils of network partitions 網絡分割技術系列
  • A Comprehensive Guide to Building a Scalable Web App on Amazon Web Services 在AWS上構建大型Web APP指南 進行中
  • How Instacart Built Its On-Demand Grocery Delivery Service Instacart背后的技術
  • Pinnability: Machine learning in the home feedPinterest主頁的機器學習
  • The Rise of the API-based SaaS API作為Saas興起
  • 5 AWS mistakes you should avoid 5個該避免的AWS錯誤
  • The Art of the Commit 提交的藝術 進行中
  • Stack Overflow: The ArchitectureStack Overflow 2016最新架構探秘
  • Scaling Knowledge at Airbnb Airbnb的知識管理 已翻
  • How Uber Thinks About Site Reliability Engineering Uber SRE怎么做
  • basic infrastructure patterns 基礎架構模式
  • Designing Schemaless, Uber Engineering Uber無模式數據存儲
  • Data Architecture in an Anti-Fraud Architecture 反欺詐系統的數據架構 進行中
  • The Epic Story of Dropbox’s Exodus From the Amazon Cloud Empire長夜讀|Dropbox 出走亞馬遜云服務帝國的壯麗史詩
  • How Badoo saved one million dollars switching to PHP7 升級PHP7省了百萬美金
  • Engineers Shouldn't Write ETL: A Guide to Building a High Functioning Data Science Department 不要寫ETL
  • Jeff Dean on Large-Scale Deep Learning at Google 已翻
  • Putting the Squeeze on Trip Data Uber技術
  • 3 simple reasons why you need to learn Scala 學習Scala的原因
  • P-values not quite considered harmful P值的作用
  • 4 reasons why microservices resonate 微模式
  • Object-oriented vs. functional programming 面向對象還是面向函數
  • Why a pattern language for microservices? 微模式的設計語言
  • Working at Netflix 在Netflix工作
  • Managing Machines at Spotify Spotify如何管理機器
  • Reclaiming Design Patterns (20 Years Later) ·設計模式20年后
  • continuous-deployment-at-instagram
  • Notes on Google's Site Reliability Engineering book
  • Apache Spark as a Compiler: Joining a Billion Rows per Second on a Laptop
  • Engineering Intelligence Through Data Visualization at Uber
  • Distribunomicon
  • 2. 大數據和數據科學系列

  • Stream processing, Event sourcing, Reactive and making sense of it all 流處理,事件源,響應式
  • Using logs to build a solid data infrastructure (or: why dual writes are a bad idea) 使用日志作為可靠數據架構
  • Bottled Water: Real-time integration of PostgreSQL and Kafka 跟PostgreSQL,Kafka做實時集成
  • Real-time full-text search with Luwak and Samza Luwak和Samza做實時全文檢索
  • Turning the database inside-out with Apache Samza Samza調優數據庫
  • Apache Kafka, Samza, and the Unix Philosophy of Distributed Data Kafka,Samza和Unix的分布式數據設計哲學
  • The value of Apache Kafka in Big Data ecosystem Kafka在大數據生態系統中的價值 已翻
  • Distributed Consensus Reloaded: Apache ZooKeeper and Replication in Apache Kafka 分布式重載:kafka中的zookeeper和復制
  • Putting Apache Kafka To Use: A Practical Guide to Building a Stream Data Platform (Part 1)使用Apache Kafka構建流式數據平臺(1)
  • Putting Apache Kafka To Use: A Practical Guide to Building a Stream Data Platform (Part 2)
  • Announcing Kafka Connect: Building large-scale low-latency data pipelines Kafka連接:搭建大規模低延遲的數據管道
  • Introducing Kafka Streams: Stream Processing Made Simple Kafka數據流:讓流處理更輕松
  • Building a high-throughput data science machine 搭建高吞吐的數據科學機器
  • The Hadoop tipping point hadoop轉折點
  • Democratizing business analytics 民主化商業分析
  • Why your next analytics project should be in procurement 分析項目采購
  • Best practices for data lakes 數據湖的最佳實踐
  • Embeddable data transformation for real-time streams 實時流的數據處理
  • Data, technology, and the future of play 數據,技術和未來游戲
  • Learning in higher dimensions 在更高維度學習
  • Hadoop in the cloud 云端的Hadoop
  • Approaching big data from a business perspective 從商業角度看大數據
  • Oil, Gas, and Data 石油,天然氣,數據
  • Designing great data products 設計偉大的數據產品
  • Doing Data Science Right Your Most Common Questions Answered 做好數據科學的常見問題
  • How BuzzFeed Thinks About Data Science Buzzfeed數據科學的思考,進行中
  • What to look for in a data scientist 數據科學家需要的
  • Statistics for Software
  • 3. 招聘&面試

  • What I Learned from Blowing An Interview 從一次失敗的面試學到的東西
  • The Trick Max Levchin Used to Hire the Best Engineers at PayPal Paypal CTO如何招聘最好工程師,完成
  • How to Hire a Rock Star Engineer 如何招聘頂級工程師
  • My favorite interview question 我最喜歡的面試題
  • What-are-the-questions-that-can-be-asked-when-the-interviewer-asks-Any-questions 還有什么問題要問
  • On Interviewing Software Engineers 怎么面試工程師
  • Ace the coding interview, every time 攻克代碼面試
  • How Stack Overflow Does Technical Interviews Stack Overflow怎么做技術面試
  • This Is How You Identify A-Players (In About 10 Minutes) During An Interview 在面試10分鐘內找到最好的人
  • Startup Interviewing is Fucked 創業公司面試
  • How to Hire 怎么招聘
  • 3 Tips for Onboarding New Hires Using Quip 新人報道指南

  • Firing People 如何開除

  • Layoffs 怎么知道會被解雇

  • Effective Code Reviews 高效代碼審查

  • Improving Our Engineering Interview Process 改進工程面試流程

  • i-quit-hiring-is-broken

  • This Startup Has a Radical Way to Encourage Work-Life Balance For Its People

  • Hiring is Broken... And It Isn't Worth Fixing

  • three-years-in-san-francisco


  • 4. 管理&成長

  • How to get rich in tech, guaranteed. 怎么通過技術變富 已翻
  • Fail at Scale 快速變化中的可靠性
  • When I Learned That Computers Have Soul 計算機有沒有靈魂
  • #define CTO 定義CTO
  • Do the Right Thing 做正確的事情
  • The Surprising Secret to Being a Good Boss 成為好老板的秘訣
  • The Highest-Leverage Activities Aren't Always Deep Work 影響力大的工作不一定有多深
  • The Secret to Growing Your Engineering Career If You Don't Want to Manage 不走管理路線你還能職業發展的秘密
  • Calculating the Value of Time: How Much is Your Time Really Worth?過去的時間管理都弱爆了!看硅谷人如何為自己的一小時定價
  • The software engineer’s guide to asserting dominance in the workplace 工程師一周應該怎么過
  • Sleep deprivation is not a badge of honor 不要熬夜
  • What is Craftsmanship and Why is it Important? 技術精益重要性
  • Being data-driven: It‘s all about the culture 數據驅動
  • Five principles for applying data science for social good
  • Beyond the Venn diagram 超越Venn類型
  • What I learned about software architecture from running a marathon 從馬拉松想到軟件架構
  • Defining a reactive microservice 定義微服務
  • Educating data 教育數據
  • Make Money Need Practice 賺錢需要經驗
  • It's Okay Not To Lead 不當老大也沒事
  • Autobiography of Blind Programmer 盲人程序員自傳
  • Those entry level startup jobs they are now mostly dead ends 初級創業公司工作死路一條
  • Everything is possible but nothing is free 一切皆有可能,但沒有免費午餐
  • Salary in my Startup: a Thought Experiment 創業公司薪水揭秘
  • Coding Like a Girl 女孩怎么編程
  • Art and Math and Science, Oh My! 藝術,數學和科學 已翻
  • The Munger Operating System: A Life That Really Works
  • 5. 創業分享

  • my-y-combinator-experience我的Y COMBINATOR 之旅
  • How to Design a Better Pitch Deck如何設計出更好的融資PPT?
  • How to build a good onboarding process for new hires at a startup創業公司如何培訓新員工
  • How I validated my startup ideazhuanlan.zhihu.com/p/20
  • After the Layoffs 裁員之后
  • 156 Startup Failure Post-Mortems 156家創業失敗啟示,1/3完成
  • 10 tips for moving from programmer to entrepreneur 從程序員進化到企業家 進行中
  • When to join a startup 什么時候加入創業公司 譯完
  • Letter To A Young Programmer Considering A Startup 給想創業的年輕程序員的信
  • How to Time TravelAirbnb CEO告訴你如何寫一篇優秀的品牌(軟)文
  • Ten classic books that define tech 十本書推薦
  • How do you validate your startup idea before quitting your current job 在你辭職前如何驗證創業想法
  • 6 questions every founder should ask before they raise capital 融資前要問的6個問題
  • The Best Time to Invest Startup 投資創業公司最佳時候
  • Ideas for Small Business 一個人的公司
  • Instagram Investment Instagram早期投資人
  • The New Rules of Startup Fundraising 創業融資的新規則
  • From side project to 250 million daily requests 從兼職項目到2.5億次日訪問
  • Up or Out: Solving the IT Turnover Crisis
  • elevate-yourself-with-side-projects
  • 6. 行業公司和人物采訪

  • Head of Amazon Web Services on Finding the Next Great Opportunity AWS主管尋找下一個偉大計劃
  • 10-lessons-from-10-years-of-awsAWS 運營 10 周年學到的 10 條經驗教訓
  • Mark Zuckerberg tackles question on what he would do as Twitter CEO如果扎克伯格是Twitter的CEO,他會怎么做?
  • How Zenefits Crashed Back Down To Earth謊言、酒宴:融資5.8億美元的硅谷獨角獸,瘋狂失控中
  • Why I left the best job in the world The Startup 為何我離開世界上最好的工作
  • A Decade at Google 在Google工作十年的感悟
  • Hadoop creator Doug Cutting on evolving and succeeding in open source Doug 談Hadoop進化和開源
  • Google and Facebook Team Up to Open Source the Gear Behind Their Empires Google 和FB談數據中心的較量 進行中
  • Facebook Doesn’t Make as Much Money as It Could Facebook錢還沒賺夠
  • What My PhD Was Like 讀博是怎么過的
  • What Technology Will Look Like In Five Years 5年后技術什么樣 翻譯完
  • Etsy CTO Q&A: We Need Software Engineers, Not Developers 我們要的是工程師,不是開發者
  • Curation and Algorithms 人工挑選和算法
  • 10X Durability 10倍可靠
  • We’re in a brave, new post open source world 在開源世界中生存
  • From fleeing Vietnam in a refugee boat to becoming Uber’s CTO從難民到Uber首席技術官:一個幸存者的故事
  • What Will You Do After White-Collar Work? 白領工作后能做啥?
  • Lyft To Uber: The Race Is On Lyft和Uber的戰爭
  • How Jeff Bezos Became a Power Beyond Amazon突破Amazon,Jeff Bezos非凡影響力的崛起之路
  • Searching For Google CEO Sundar Pichai, The Most Powerful Tech Giant You've Never Heard Of Google CEO你沒聽說過的超強巨人
  • Why This Tech Bubble is Worse Than the Tech Bubble of 2000 現在科技泡沫比2000年還大?
  • The sharing economy: A big step toward making Marshall McLuhan's Global Village a reality 共享經濟
  • Algorithms of the Mind 思想的算法
  • The inside story of how Amazon created Echo, the next billion-dollar business no one saw coming亞馬遜 Echo 誕生記:起初無人看好,如今它卻擁有十億美元的商機
  • Three Lessons On Innovation I Learned During My 12 Years At Apple在蘋果工作12年,職場老兵告訴你如何創新
  • Linux at 25: Q&A With Linus TorvaldsLinux 25 歲了,我采訪了大神 Linus
  • Founder of Pandora on Lessons from Near Dot Com Bust to Billion Dollar IPO Pandora從破產到十億俱樂部
  • WeWork’s Radical Plan to Remake Real Estate With Code WeWork顛覆房地產
  • MY YEAR IN STARTUP HELL 50歲在創業公司
  • The Story Behind Siri 聽“Siri之父”講述Siri背后的故事
  • Building Internet Startup Chinese Style 互聯網創業要像中國學習
  • bloomberg.com/features/
  • Inside Palantir, Silicon Valley's Most Secretive Company
  • Inside OpenAI, Elon Musk’s Wild Plan to Set Artificial Intelligence Free
  • interivew-with-shantanu-sinha
  • Inside Evan Spiegel's very private Snapchat Story
  • Andrew Ng: Why ‘Deep Learning’ Is a Mandate for Humans, Not Just Machines
  • 'I was losing $1 million a day, every day for 18 months': Meet Chris Anderson, the man behind TED talks
  • 7. 人工智能&機器學習

  • How AI Is Feeding China s Internet Dragon AI是怎么適應中國互聯網巨龍的(百度)
  • Silicon Valley Looks to Artificial Intelligence for the Next Big Thing 硅谷把AI作為下一個大事
  • Artificial Intelligence Finally Entered Our Everyday World AI最后進入我們每天的生活
  • The Future of Chat Is not AI 聊天的未來不是AI
  • AlphaGo and the Limits of Machine Intuition AlphaGo和機器覺醒
  • The current state of machine intelligence 2.0重磅機器智能 2.0 生態圖譜
  • The future of machine intelligenceO’Reilly 報告:機器智能的未來
  • Learning from Tay Tay學到的
  • Learning from AlphaGo AlphaGo學習到的
  • Risto Miikkulainen on evolutionary computation and making robots think for themselves 如何讓機器人自我思考
  • How to build and run your first deep learning network 怎么搭建第一個深度學習網絡
  • Predictive modeling: Striking a balance between accuracy and interpretability
  • How human-machine collaboration has automated the data catalog 人工和機器如何合作生成數據目錄
  • Building a business that combines human experts and data science 把專家和數據科學結合
  • Unsupervised learning, attention, and other mysteries 非監督學習,注意和其他神秘
  • AI‘s dueling definitions AI的定義
  • In search of a model for modeling intelligence 模型智能的搜索
  • What is deep learning, and why should you care? 深度學習是啥
  • Compressed representations in the age of big data 大數據時代的壓縮表示
  • Machine learning in the wild 機器學習野蠻生長
  • Training and serving NLP models using Spark MLlib 通過spark庫做自然語言處理
  • Wouldn‘t it be fun to build your own Google? 能自己建個Google嗎
  • Small brains, big data 小大腦,大數據
  • On the evolution of machine learning 機器學習的進化
  • Evolutionary computation: Stepping stones and unexpected solutions 進化計算
  • Data has a shape 數據有型
  • Geoffrey Hinton, the 'godfather' of deep learning, on AlphaGo前沿 | 專訪Geoffrey Hinton:人工智能會繼續發展,請不要誤用
  • Million-dollar babies 硅谷為了搶人,做AI的學生有福了
  • Uber CTO reveals how Travis Kalanick hired him and offers advice for entrepreneurs Uber CTO揭秘招聘和對企業家建議
  • My path to OpenAI
  • 8. 產品設計&用戶增長

  • How Slack Uses Slack Slack是如何使用Slack的
  • The Design Sprint 設計的周期
  • On building product at Medium Medium如何做產品的
  • Duolinguo reach 110M Users 多鄰國怎么把用戶發展到上億的 ,已翻
  • Simple Design is What You Need, Not What You Want 簡單設計你需要的,而不是想要的
  • Growth is a system, not a bag of tricks 增長是一個系統
  • Design, Process, and Collaboration at Stripe Stripe設計,流程和合作
  • Product Hunt Rise Product Hunt 花了3年多成長故事
  • The Rise, Fall, and Rise of Bitly: How a Free Link Shortener Became a Real Business Adventures in Consumer Technology 短鏈服務如何掙錢的
  • How Apple Built 3D Touch 蘋果手機的3D觸摸怎么做的
  • Hacking Word-of-Mouth: Making Referrals Work for Airbnb[Growth Hacking] Airbnb 邀請系統的實現過程
  • How Pinterest increased MAUs with one simple trick Pinterest實現MAU增長的小技巧
  • The vision, mission, and strategy for Coinbase Coinbase的使命和戰略
  • Mobile UX Design: What Makes a Good Notification? 手機UX設計:怎么做好通知
  • Joel Marsh on the science of design 設計科學
  • UX for beginners: Key ideas UX入門
  • Prototyping for physical and digital products 物理數字產品的原型設計
  • Snapchat's Ladder Snapchat的梯子
  • Freemium Conversion Rate: Why Spotify Destroys Dropbox by 667% Spotify的轉化率
  • The Story of AdMob: How One MBA Dropout Sold His Business to Google for $750 million AdMob 賣給Google 7.5億
  • Why Facebook And Mark Zuckerberg Went All In On Live Video Facebook為何全力做視頻直播
  • Y Combinator and The One Metric that Matters 集中在一個指標上
  • Instagram and Facebook are Dead Instagram和Facebook都死了
  • Instagram is stupid Instagram太傻了
  • The Scientific Marketing Strategy Behind Exponential Growth
  • 9. 前沿技術(虛擬現實,實時計算)

  • Timoni West on nailing the virtual reality user experience 虛擬現實體驗
  • The evolution of open source is a good thing 開源進化是好事
  • A new infrastructure for biology 生物的新架構
  • The IoT is a natural ecosystem for streaming analytics IOT是流分析的自然生態
  • Stream processing and messaging systems for the IoT age IOT的實時消息處理
  • Embeddable data transformation for real-time streams 實時流計算
  • The big data market從Hadoop洞悉大數據市場:路漫漫其修遠兮
  • What‘ next for big data applications? 下一個大數據應用是什么
  • Distributed systems performance solutions require real-time intelligence 分布式系統需要實時智能

  • 10. 其他

  • Chinese Scions’ Song: My Daddy’s Rich and My Lamborghini’s Good-Looking 老爸很有錢,蘭博基尼很酷
  • The long march from China to the Ivies 中國學生進入哈佛的長征之路
  • Priscilla Chan, in rare interview, tells how her goals with Mark Zuckerberg are shaped by personal story她讓扎克伯格死心塌地,原因就兩個字
  • Heavy Recruitment of Chinese Students Sows Discord on U.S. Campuses 美國大學招了太多中國學生
  • The American Scholar: Saving the Self in the Age of the Selfie 不要再自拍了
  • “I had so many advantages, and I barely made it”: Pinterest engineer on Silicon Valley
  • How To Manage Developers When You're A Non-Tech Founder
  • How to be the most productive person in your office a€” and still get home by 5:30 p.m.
  • ------------------

    關注如下我的微信公眾號“董老師在硅谷”,關注硅谷趨勢,一起學習成長。


    作者:董飛
    鏈接:https://zhuanlan.zhihu.com/p/20472545
    來源:知乎

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