2016年科技阅读列表

之前整理的2015年科技阅读列表［600篇］，有人觉得看不过来，我就把一些个人喜欢的重新列出来，再加到今年列表中，慢慢补充，加上分类标签，欢迎大家留言翻译。比如时间在几周内，站内联系。更新 2016/05/23

1. 技术架构

1. Everyday Algorithms: Elevator Allocation 电梯算法调度
   
2. Le Cloud Blog 系统设计系列 scalability入门
   
3. Airbnb Shares The Keys To Its Infrastructure Airbnb基础架构 翻完
4. Backend infrastructure at Spotify Spotify架构
5. Jepsen: On the perils of network partitions 网络分割技术系列
6. A Comprehensive Guide to Building a Scalable Web App on Amazon Web Services 在AWS上构建大型Web APP指南 进行中
7. How Instacart Built Its On-Demand Grocery Delivery Service Instacart背后的技术
8. Pinnability: Machine learning in the home feedPinterest主页的机器学习
   
9. The Rise of the API-based SaaS API作为Saas兴起
10. 5 AWS mistakes you should avoid 5个该避免的AWS错误
    
11. The Art of the Commit 提交的艺术 进行中
    
12. Stack Overflow: The ArchitectureStack Overflow 2016最新架构探秘
13. Scaling Knowledge at Airbnb Airbnb的知识管理 已翻
14. How Uber Thinks About Site Reliability Engineering Uber SRE怎么做
    
15. basic infrastructure patterns 基础架构模式
    
16. Designing Schemaless, Uber Engineering Uber无模式数据存储
    
17. Data Architecture in an Anti-Fraud Architecture 反欺诈系统的数据架构 进行中
    
18. The Epic Story of Dropbox’s Exodus From the Amazon Cloud Empire长夜读|Dropbox 出走亚马逊云服务帝国的壮丽史诗
    
19. How Badoo saved one million dollars switching to PHP7 升级PHP7省了百万美金
    
20. Engineers Shouldn't Write ETL: A Guide to Building a High Functioning Data Science Department 不要写ETL
    
21. Jeff Dean on Large-Scale Deep Learning at Google 已翻
    
22. Putting the Squeeze on Trip Data Uber技术
    
23. 3 simple reasons why you need to learn Scala 学习Scala的原因
    
24. P-values not quite considered harmful P值的作用
    
25. 4 reasons why microservices resonate 微模式
    
26. Object-oriented vs. functional programming 面向对象还是面向函数
    
27. Why a pattern language for microservices? 微模式的设计语言
28. Working at Netflix 在Netflix工作
    
29. Managing Machines at Spotify Spotify如何管理机器
    
30. Reclaiming Design Patterns (20 Years Later) ·设计模式20年后
    
31. continuous-deployment-at-instagram
    
32. Notes on Google's Site Reliability Engineering book
    
33. Apache Spark as a Compiler: Joining a Billion Rows per Second on a Laptop
34. Engineering Intelligence Through Data Visualization at Uber
35. Distribunomicon

2. 大数据和数据科学系列

1. Stream processing, Event sourcing, Reactive and making sense of it all 流处理，事件源，响应式
   
2. Using logs to build a solid data infrastructure (or: why dual writes are a bad idea) 使用日志作为可靠数据架构
   
3. Bottled Water: Real-time integration of PostgreSQL and Kafka 跟PostgreSQL，Kafka做实时集成
   
4. Real-time full-text search with Luwak and Samza Luwak和Samza做实时全文检索
   
5. Turning the database inside-out with Apache Samza Samza调优数据库
   
6. Apache Kafka, Samza, and the Unix Philosophy of Distributed Data Kafka，Samza和Unix的分布式数据设计哲学
7. The value of Apache Kafka in Big Data ecosystem Kafka在大数据生态系统中的价值 已翻
8. Distributed Consensus Reloaded: Apache ZooKeeper and Replication in Apache Kafka 分布式重载：kafka中的zookeeper和复制
9. Putting Apache Kafka To Use: A Practical Guide to Building a Stream Data Platform (Part 1)使用Apache Kafka构建流式数据平台（1）
10. Putting Apache Kafka To Use: A Practical Guide to Building a Stream Data Platform (Part 2)
11. Announcing Kafka Connect: Building large-scale low-latency data pipelines Kafka连接：搭建大规模低延迟的数据管道
12. Introducing Kafka Streams: Stream Processing Made Simple Kafka数据流：让流处理更轻松
13. Building a high-throughput data science machine 搭建高吞吐的数据科学机器
    
14. The Hadoop tipping point hadoop转折点
    
15. Democratizing business analytics 民主化商业分析
    
16. Why your next analytics project should be in procurement 分析项目采购
    
17. Best practices for data lakes 数据湖的最佳实践
    
18. Embeddable data transformation for real-time streams 实时流的数据处理
    
19. Data, technology, and the future of play 数据，技术和未来游戏
    
20. Learning in higher dimensions 在更高维度学习
    
21. Hadoop in the cloud 云端的Hadoop
22. Approaching big data from a business perspective 从商业角度看大数据
    
23. Oil, Gas, and Data 石油，天然气，数据
    
24. Designing great data products 设计伟大的数据产品
    
25. Doing Data Science Right Your Most Common Questions Answered 做好数据科学的常见问题
    
26. How BuzzFeed Thinks About Data Science Buzzfeed数据科学的思考，进行中
27. What to look for in a data scientist 数据科学家需要的
    
28. Statistics for Software
    

3. 招聘&面试

1. What I Learned from Blowing An Interview 从一次失败的面试学到的东西
2. The Trick Max Levchin Used to Hire the Best Engineers at PayPal Paypal CTO如何招聘最好工程师，完成
3. How to Hire a Rock Star Engineer 如何招聘顶级工程师
4. My favorite interview question 我最喜欢的面试题
5. What-are-the-questions-that-can-be-asked-when-the-interviewer-asks-Any-questions 还有什么问题要问
6. On Interviewing Software Engineers 怎么面试工程师
7. Ace the coding interview, every time 攻克代码面试
   
8. How Stack Overflow Does Technical Interviews Stack Overflow怎么做技术面试
9. This Is How You Identify A-Players (In About 10 Minutes) During An Interview 在面试10分钟内找到最好的人
10. Startup Interviewing is Fucked 创业公司面试
    
11. How to Hire 怎么招聘

12. 3 Tips for Onboarding New Hires Using Quip 新人报道指南

13. Firing People 如何开除
    

14. Layoffs 怎么知道会被解雇
    

15. Effective Code Reviews 高效代码审查
    

16. Improving Our Engineering Interview Process 改进工程面试流程
    

17. i-quit-hiring-is-broken
    

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

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

20. three-years-in-san-francisco
    

    
    

4. 管理&成长

1. How to get rich in tech, guaranteed. 怎么通过技术变富 已翻
2. Fail at Scale 快速变化中的可靠性
3. When I Learned That Computers Have Soul 计算机有没有灵魂
   
4. #define CTO 定义CTO
5. Do the Right Thing 做正确的事情
   
6. The Surprising Secret to Being a Good Boss 成为好老板的秘诀
   
7. The Highest-Leverage Activities Aren't Always Deep Work 影响力大的工作不一定有多深
   
8. The Secret to Growing Your Engineering Career If You Don't Want to Manage 不走管理路线你还能职业发展的秘密
9. Calculating the Value of Time: How Much is Your Time Really Worth?过去的时间管理都弱爆了！看硅谷人如何为自己的一小时定价
10. The software engineer’s guide to asserting dominance in the workplace 工程师一周应该怎么过
11. Sleep deprivation is not a badge of honor 不要熬夜
    
12. What is Craftsmanship and Why is it Important? 技术精益重要性
    
13. Being data-driven: It‘s all about the culture 数据驱动
    
14. Five principles for applying data science for social good
    
15. Beyond the Venn diagram 超越Venn类型
    
16. What I learned about software architecture from running a marathon 从马拉松想到软件架构
    
17. Defining a reactive microservice 定义微服务
    
18. Educating data 教育数据
    
19. Make Money Need Practice 赚钱需要经验
    
20. It's Okay Not To Lead 不当老大也没事
    
21. Autobiography of Blind Programmer 盲人程序员自传
    
22. Those entry level startup jobs they are now mostly dead ends 初级创业公司工作死路一条
    
23. Everything is possible but nothing is free 一切皆有可能，但没有免费午餐
    
24. Salary in my Startup: a Thought Experiment 创业公司薪水揭秘
    
25. Coding Like a Girl 女孩怎么编程
    
26. Art and Math and Science, Oh My! 艺术，数学和科学 已翻
    
27. The Munger Operating System: A Life That Really Works
    

5. 创业分享

1. my-y-combinator-experience我的Y COMBINATOR 之旅
2. How to Design a Better Pitch Deck如何设计出更好的融资PPT？
3. How to build a good onboarding process for new hires at a startup创业公司如何培训新员工
4. How I validated my startup ideahttp://zhuanlan.zhihu.com/p/20695649?refer=donglaoshi
5. After the Layoffs 裁员之后
6. 156 Startup Failure Post-Mortems 156家创业失败启示，1/3完成
   
7. 10 tips for moving from programmer to entrepreneur 从程序员进化到企业家 进行中
   
8. When to join a startup 什么时候加入创业公司 译完
   
9. Letter To A Young Programmer Considering A Startup 给想创业的年轻程序员的信
   
10. How to Time TravelAirbnb CEO告诉你如何写一篇优秀的品牌（软）文
11. Ten classic books that define tech 十本书推荐
12. How do you validate your startup idea before quitting your current job 在你辞职前如何验证创业想法
    
13. 6 questions every founder should ask before they raise capital 融资前要问的6个问题
    
14. The Best Time to Invest Startup 投资创业公司最佳时候
    
15. Ideas for Small Business 一个人的公司
    
16. Instagram Investment Instagram早期投资人
    
17. The New Rules of Startup Fundraising 创业融资的新规则
    
18. From side project to 250 million daily requests 从兼职项目到2.5亿次日访问
    
19. Up or Out: Solving the IT Turnover Crisis
    
20. elevate-yourself-with-side-projects

6. 行业公司和人物采访

1. Head of Amazon Web Services on Finding the Next Great Opportunity AWS主管寻找下一个伟大计划
2. 10-lessons-from-10-years-of-awsAWS 运营 10 周年学到的 10 条经验教训
   
3. Mark Zuckerberg tackles question on what he would do as Twitter CEO如果扎克伯格是Twitter的CEO，他会怎么做？
4. How Zenefits Crashed Back Down To Earth谎言、酒宴：融资5.8亿美元的硅谷独角兽，疯狂失控中
5. Why I left the best job in the world The Startup 为何我离开世界上最好的工作
6. A Decade at Google 在Google工作十年的感悟
7. Hadoop creator Doug Cutting on evolving and succeeding in open source Doug 谈Hadoop进化和开源
8. Google and Facebook Team Up to Open Source the Gear Behind Their Empires Google 和FB谈数据中心的较量 进行中
   
9. Facebook Doesn’t Make as Much Money as It Could Facebook钱还没赚够
10. What My PhD Was Like 读博是怎么过的
    
11. What Technology Will Look Like In Five Years 5年后技术什么样 翻译完
12. Etsy CTO Q&A: We Need Software Engineers, Not Developers 我们要的是工程师，不是开发者
13. Curation and Algorithms 人工挑选和算法
    
14. 10X Durability 10倍可靠
15. We’re in a brave, new post open source world 在开源世界中生存
    
16. From fleeing Vietnam in a refugee boat to becoming Uber’s CTO从难民到Uber首席技术官：一个幸存者的故事
    
17. What Will You Do After White-Collar Work? 白领工作后能做啥？
18. Lyft To Uber: The Race Is On Lyft和Uber的战争
19. How Jeff Bezos Became a Power Beyond Amazon突破Amazon，Jeff Bezos非凡影响力的崛起之路
    
20. Searching For Google CEO Sundar Pichai, The Most Powerful Tech Giant You've Never Heard Of Google CEO你没听说过的超强巨人
21. Why This Tech Bubble is Worse Than the Tech Bubble of 2000 现在科技泡沫比2000年还大？
    
22. The sharing economy: A big step toward making Marshall McLuhan's Global Village a reality 共享经济
23. Algorithms of the Mind 思想的算法
    
24. The inside story of how Amazon created Echo, the next billion-dollar business no one saw coming亚马逊 Echo 诞生记：起初无人看好，如今它却拥有十亿美元的商机
    
25. Three Lessons On Innovation I Learned During My 12 Years At Apple在苹果工作12年，职场老兵告诉你如何创新
26. Linux at 25: Q&A With Linus TorvaldsLinux 25 岁了，我采访了大神 Linus
    
27. Founder of Pandora on Lessons from Near Dot Com Bust to Billion Dollar IPO Pandora从破产到十亿俱乐部
28. WeWork’s Radical Plan to Remake Real Estate With Code WeWork颠覆房地产
    
29. MY YEAR IN STARTUP HELL 50岁在创业公司
    
30. The Story Behind Siri 听“Siri之父”讲述Siri背后的故事
31. Building Internet Startup Chinese Style 互联网创业要像中国学习
    
32. http://www.bloomberg.com/features/2016-amazon-echo/
    
33. Inside Palantir, Silicon Valley's Most Secretive Company
    
34. Inside OpenAI, Elon Musk’s Wild Plan to Set Artificial Intelligence Free
    
35. interivew-with-shantanu-sinha
    
36. Inside Evan Spiegel's very private Snapchat Story
37. Andrew Ng: Why ‘Deep Learning’ Is a Mandate for Humans, Not Just Machines
38. '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&机器学习

1. How AI Is Feeding China s Internet Dragon AI是怎么适应中国互联网巨龙的（百度）
   
2. Silicon Valley Looks to Artificial Intelligence for the Next Big Thing 硅谷把AI作为下一个大事
3. Artificial Intelligence Finally Entered Our Everyday World AI最后进入我们每天的生活
4. The Future of Chat Is not AI 聊天的未来不是AI
5. AlphaGo and the Limits of Machine Intuition AlphaGo和机器觉醒
   
6. The current state of machine intelligence 2.0重磅机器智能 2.0 生态图谱
7. The future of machine intelligenceO’Reilly 报告：机器智能的未来
8. Learning from Tay Tay学到的
9. Learning from AlphaGo AlphaGo学习到的
   
10. Risto Miikkulainen on evolutionary computation and making robots think for themselves 如何让机器人自我思考
    
11. How to build and run your first deep learning network 怎么搭建第一个深度学习网络
    
12. Predictive modeling: Striking a balance between accuracy and interpretability
    
13. How human-machine collaboration has automated the data catalog 人工和机器如何合作生成数据目录
    
14. Building a business that combines human experts and data science 把专家和数据科学结合
    
15. Unsupervised learning, attention, and other mysteries 非监督学习，注意和其他神秘
    
16. AI‘s dueling definitions AI的定义
    
17. In search of a model for modeling intelligence 模型智能的搜索
    
18. What is deep learning, and why should you care? 深度学习是啥
    
19. Compressed representations in the age of big data 大数据时代的压缩表示
    
20. Machine learning in the wild 机器学习野蛮生长
    
21. Training and serving NLP models using Spark MLlib 通过spark库做自然语言处理
    
22. Wouldn‘t it be fun to build your own Google? 能自己建个Google吗
    
23. Small brains, big data 小大脑，大数据
    
24. On the evolution of machine learning 机器学习的进化
    
25. Evolutionary computation: Stepping stones and unexpected solutions 进化计算
    
26. Data has a shape 数据有型
    
27. Geoffrey Hinton, the 'godfather' of deep learning, on AlphaGo前沿 | 专访Geoffrey Hinton：人工智能会继续发展，请不要误用
    
28. Million-dollar babies 硅谷为了抢人，做AI的学生有福了
    
29. Uber CTO reveals how Travis Kalanick hired him and offers advice for entrepreneurs Uber CTO揭秘招聘和对企业家建议
    
30. My path to OpenAI
    

8. 产品设计&用户增长

1. How Slack Uses Slack Slack是如何使用Slack的
2. The Design Sprint 设计的周期
3. On building product at Medium Medium如何做产品的
4. Duolinguo reach 110M Users 多邻国怎么把用户发展到上亿的 ，已翻
   
5. Simple Design is What You Need, Not What You Want 简单设计你需要的，而不是想要的
   
6. Growth is a system, not a bag of tricks 增长是一个系统
7. Design, Process, and Collaboration at Stripe Stripe设计，流程和合作
8. Product Hunt Rise Product Hunt 花了3年多成长故事
   
9. The Rise, Fall, and Rise of Bitly: How a Free Link Shortener Became a Real Business Adventures in Consumer Technology 短链服务如何挣钱的
   
10. How Apple Built 3D Touch 苹果手机的3D触摸怎么做的
11. Hacking Word-of-Mouth: Making Referrals Work for Airbnb[Growth Hacking] Airbnb 邀请系统的实现过程
    
12. How Pinterest increased MAUs with one simple trick Pinterest实现MAU增长的小技巧
    
13. The vision, mission, and strategy for Coinbase Coinbase的使命和战略
    
14. Mobile UX Design: What Makes a Good Notification? 手机UX设计：怎么做好通知
    
15. Joel Marsh on the science of design 设计科学
    
16. UX for beginners: Key ideas UX入门
    
17. Prototyping for physical and digital products 物理数字产品的原型设计
    
18. Snapchat's Ladder Snapchat的梯子
    
19. Freemium Conversion Rate: Why Spotify Destroys Dropbox by 667% Spotify的转化率
    
20. The Story of AdMob: How One MBA Dropout Sold His Business to Google for $750 million AdMob 卖给Google 7.5亿
    
21. Why Facebook And Mark Zuckerberg Went All In On Live Video Facebook为何全力做视频直播
    
22. Y Combinator and The One Metric that Matters 集中在一个指标上
23. Instagram and Facebook are Dead Instagram和Facebook都死了
    
24. Instagram is stupid Instagram太傻了
    
25. The Scientific Marketing Strategy Behind Exponential Growth
    

9. 前沿技术（虚拟现实，实时计算）

1. Timoni West on nailing the virtual reality user experience 虚拟现实体验
   
2. The evolution of open source is a good thing 开源进化是好事
   
3. A new infrastructure for biology 生物的新架构
   
4. The IoT is a natural ecosystem for streaming analytics IOT是流分析的自然生态
   
5. Stream processing and messaging systems for the IoT age IOT的实时消息处理
   
6. Embeddable data transformation for real-time streams 实时流计算
7. The big data market从Hadoop洞悉大数据市场：路漫漫其修远兮
   
8. What‘ next for big data applications? 下一个大数据应用是什么
9. Distributed systems performance solutions require real-time intelligence 分布式系统需要实时智能

10. 其他

1. Chinese Scions’ Song: My Daddy’s Rich and My Lamborghini’s Good-Looking 老爸很有钱，兰博基尼很酷
   
2. The long march from China to the Ivies 中国学生进入哈佛的长征之路
3. Priscilla Chan, in rare interview, tells how her goals with Mark Zuckerberg are shaped by personal story她让扎克伯格死心塌地，原因就两个字
4. Heavy Recruitment of Chinese Students Sows Discord on U.S. Campuses 美国大学招了太多中国学生
5. The American Scholar: Saving the Self in the Age of the Selfie 不要再自拍了
6. “I had so many advantages, and I barely made it”: Pinterest engineer on Silicon Valley
   
7. How To Manage Developers When You're A Non-Tech Founder
   
8. How to be the most productive person in your office — and still get home by 5:30 p.m.
   

－－－－－－－－－－－－－－－－－－

关注如下我的微信公众号“董老师在硅谷”，关注硅谷趋势，一起学习成长。

作者：董飞
链接：https://zhuanlan.zhihu.com/p/20472545
来源：知乎