Slicing Pie: Funding Your Company Without Funds31We80f2z1L._SX310_BO1,204,203,200_

You and a partner go into business together and split the equity 50/50. You do all the work and your partner slacks off. He owns half your business- now what?

Slicing Pie outlines a process for calculating exactly the right number of shares each founder or employee in an early stage company deserves.

You will learn:

  • How to value the time and resources an individual brings to the company relative to the contributions of others
  • The right way to value intangible things like ideas and relationships
  • What to do when a founder leaves your company
  • How to handle equity when you have to fire someone
  • Important issues to discuss with your lawyer
  • Much more

Research shows that dynamic equity split models, like the one outlined in Slicing Pie, is the best way to avoid conflicts as the company grows.

The new and improved Version 2.3 contains updated information about legal issues, idea valuation, retrofitting and much more!

The Founder’s Dilemmas: Anticipating and Avoiding the Pitfalls That Can Sink a Startup (The Kauffman Foundation Series on Innovation and  41qyfyCw3hL._SX329_BO1,204,203,200_Entrepreneurship)

Often downplayed in the excitement of starting up a new business venture is one of the most important decisions entrepreneurs will face: should they go it alone, or bring in cofounders, hires, and investors to help build the business? More than just financial rewards are at stake. Friendships and relationships can suffer. Bad decisions at the inception of a promising venture lay the foundations for its eventual ruin. The Founder’s Dilemmas is the first book to examine the early decisions by entrepreneurs that can make or break a startup and its team. Drawing on a decade of research, Noam Wasserman reveals the common pitfalls founders face and how to avoid them. He looks at whether it is a good idea to cofound with friends or relatives, how and when to split the equity within the founding team, and how to recognize when a successful founder-CEO should exit or be fired. Wasserman explains how to anticipate, avoid, or recover from disastrous mistakes that can splinter a founding team, strip founders of control, and leave founders without a financial payoff for their hard work and innovative ideas. He highlights the need at each step to strike a careful balance between controlling the startup and attracting the best resources to grow it, and demonstrates why the easy short-term choice is often the most perilous in the long term. The Founder’s Dilemmas draws on the inside stories of founders like Evan Williams of Twitter and Tim Westergren of Pandora, while mining quantitative data on almost ten thousand founders. People problems are the leading cause of failure in startups. This book offers solutions.

Venture Deals: Be Smarter Than Your Lawyer and Venture Capitalist51p0oeLn-PL._SX337_BO1,204,203,200_

As each new generation of entrepreneurs emerges, there is a renewed interest in how venture capital deals come together. Yet there is little reliable information focused on venture capital deals. Nobody understands this better than authors Brad Feld and Jason Mendelson. For more than twenty years, they’ve been involved in hundreds of venture capital financings, and now, with the Second Edition of Venture Deals, they continue to share their experiences in this field with you.

Engaging and informative, this reliable resource skillfully outlines the essential elements of the venture capital term sheet–from terms related to economics to terms related to control. It strives to give a balanced view of the particular terms along with the strategies to getting to a fair deal. In addition to examining the nuts and bolts of the term sheet, Venture Deals, Second Edition also introduces you to the various participants in the process and discusses how fundraising works.

  • Fully updated to reflect the intricacies of startups and entrepreneurship in today’s dynamic economic environment
  • Offers valuable insights into venture capital deal structure and strategies
  • Brings a level of transparency to a process that is rarely well understood

Whether you’re an experienced or aspiring entrepreneur, venture capitalist, or lawyer who partakes in these particular types of deals, you will benefit from the insights found throughout this new book.


2016-05-13 丑灿 大数据技术









Data Science forBusiness



——来自Amazon用户m I的读后感


The Art of Data Science







Big Data:Principles and Best Practices of Scalable Realtime Data Systems


——来自Amazon用户Kirk D. Borne的读后感



 Big Data Now: 2015 Edition



03.Apache HadoopDISCOVERY



Hadoop: The Definitive Guide


——来自Amazon用户AI Gordon的读后感


Hadoop Explained



04.Apache SparkDISCOVERY



 Learning Spark




《掌握Apache Spark》

Mastering Apache Spark

这本书是我们收集关于使用Apache Spark的各种具体细节的最后一块终极瑰宝。





Pattern Recognition and MachineLearning (Information Science and Statistics)





Elements of Statistical Learning


——来自Amazon用户Enceladus Transit的读后感




Python MachineLearning


——来自Amazon用户Brian M. Thomas的读后感



An Introduction to StatisticalLearning with Applications in R







Neural Networks and Deep Learning


  • 一个绚烂的受生物学启发得到的程序设计范例,可以让计算机从所观察到的数据进行相应内容的学习
  • 深度学习,神经网络中强大的学习技术




Deep Learning

这本由Ian Goodfellow,、Yoshua Bengio和Aaron Courville合著的书籍正在筹备阶段,有可能是未来最佳的关于深度学习的书籍。这本书的开发版每月都在更新,在最终出版的时候读者可以免费获取。




Data Mining:Concepts and Techniques, Third Edition





Mining of Massive Datasets





《SQL 第二版》

Learning SQL,Second Edition


——来自Amazon用户Jack D. Herrington的读后感



Learn SQL The Hard Way






Statistics inPlain English, Third Edition


——来自Amazon用户Shyam Goli的读后感


《Think Stats:程序员需要的概率论统计学,第二版》

Think Stats:Probability and Statistics for Programmers, Second Edition

Think Stats强调了让你使用简单的技术进行数据和有趣问题答案的开发。这本书介绍了美国国家卫生研究院使用数据进行的案例的研究。


Recommended Reading for Developers

Jeff Atwood

This list was last updated in March 2015.

Why are updates to my reading list so rare? Because computers change a lot in 10 years, but people don’t.

To make better software, you need to understand how people work, and that is what the books I recommend tend to focus on.

Code Complete 2


Steve McConnell’s Code Complete 2 is the Joy of Cooking for software developers. Reading it means that you enjoy your work, you’re serious about what you do, and you want to keep improving. In Code Complete, Steve notes that the average programmer reads less than one technical book per year. The very act of reading this book already sets you apart from probably ninety percent of your fellow developers. In a good way.

I like this book so much that the title of this very website is derived from it – the examples of what not to do are tagged with the “Coding Horror” icon. There’s nothing funnier than a Coding Horror – until you have to deal with one yourself. Then it’s suddenly not so funny any more. Do yourself a favor. Make this the first book you read, and the first book you recommend to your fellow developers.

The Mythical Man-Month


Arguably the only classic book in our field. If you haven’t read it, shame on you.

I challenge any developer to pick up a copy of The Mythical Man Month and not find this tale of a long-defunct OS, and the long-defunct team that developed it, startlingly relevant. This twenty-five year old book boldly illustrates one point: computers may change, but people don’t.

Reading this classic work will certainly be a better use of your time than poring over the latest thousand page technical tome du jour.

Don’t Make Me Think


The single best book on usability I’ve ever read. The title says “web usability” but don’t be fooled by its faux specificity. Steve Krug covers every important usability concept in this book, and covers it well. It’s almost fun. If you choose to read only one book on usability, choose this one. It’s chock full of great information, and it’s presented in a concise, approachable format. It’s suitable for any audience: technical, non-technical, user, developer, manager, you name it.

sample graphic from Don't Make Me Think

Er… yeah. Never been in a meeting like that. The solution to this problem, by the way, is quick and dirty usability testing. Imagine that: making decisions based on actual data instead of never ending, last man standing filibuster style religious debates. Revolutionary!

Rapid Development


The full title of this book is Rapid Development: Taming Wild Software Development Schedules, which isn’t just long-winded and vaguely ridiculous, it’s also an unfortunate misnomer.

Rapid Development isn’t about rapid development. It’s about* the reality of failure* . The vast majority of software development projects will fail: they will overrun their schedules, produce substandard results, or sometimes not even finish at all. This isn’t an argument; it’s a statistical fact. The unpleasant truth is that your team has to be very good to simply avoid failing, much less to succeed. While that may sound depressing – okay, it is depressing– you’ll still want to read this book.

Why? Because half* of success is not repeating the same mistakes you, or other people, have made. The epiphany offered in this book is that making mistakes is good– so long as they are all new, all singing, all dancing mistakes. If you’re making the same old classic mistakes, you’ve failed before you’ve even begun. And you probably have no idea how likely it is that you’re making one of these mistakes right now.

Our field is one of the few where change is the only constant, so it’s only natural to embrace that change and try different “Rapid” development techniques. But the converse isn’t true. We can’t assume that so much has changed since 1970 that all the old software development lessons are obsolete and irrelevant when compared to our hot new technology. It’s the same old story: computers have changed; people haven’t. At least have some idea of what works and what doesn’t before you start– in McConnell’s words, “read the instructions on the paint can before painting.” Sure, it sounds obvious enough until you read this book and realize how rarely that actually happens in our field.

* According to the book, technically, one-quarter. But I think it’s more than that.



If you’ve ever seen the performance of an all-star sports team suffer due to poor coaching, you’ll appreciate this book. It doesn’t matter how many “coding superstars” you’ve got when none of them can talk to each other, or agree on anything. And it no developer, however talented, can work effectively when constantly being barraged with minor interruptions. Developers aren’t known for their people skills, per se, but here’s the ironic part: the success of your project may hinge on just that. If you have any legitimate aspirations to be a “Team Leader” in practice instead of in name only, you need to pick up a copy of this book.

While Peopleware is full of great, totally valid points, it also implies a level of employee control over the workplace that is pure fantasy at most companies. But at least you’ll know when your work environment, or your team, are the real problem – and more importantly, what to do about it.

The Design of Everyday Things


It can be incredibly frustrating to develop software, because so much can go wrong. A lot of what we do is defensive: trying to anticipate what will go wrong before it does. It’s mentally fatiguing, and can eventually manifest itself in some negative ways. I sometimes describe this to non-technical people as building a watch with a thousand moving parts, all of which can fail randomly at the slightest provocation. Good times!

Designing software is difficult, to be sure, but designing a door is difficult too. The nuances of design extend into every object you touch, whether it’s some hot new SQL engine, or a humble shoe. This book will give you a new appreciation of the “devil in the details.” If designing a door isn’t the no-brainer we thought it was, maybe it’s time to give ourselves a break for not being able to design software perfectly, either.

About Face: The Essentials of Interaction Design


Alan Cooper, father of Visual Basic, godfather of usability. I’ve owned a few versions of this book now (this is version four), and it is the rare book which is getting better and better as it is revised, and more authors are added for different perspectives.

About Face is full of generally applicable guidelines for mobile and web. Of the GUI problems used for illustration – with examples from the hoary old Windows 95 UI – it’s interesting to compare which have been mostly resolved (using visual examples to show the effects of dialog selections before you make them), and which have not (stopping the proceedings with modal idiocy).

It’s a fantastically useful book; I’ve used whole chapters as guides for projects I worked on.

The Inmates Are Running the Asylum


This is the book that introduced the world to the concept of personas: rather than thinking of users as an abstract, difficult-to-describe, amorphous group of people, personas instruct us to talk about specific users who have names, personalities, needs, and goals. Would our users want a print preview feature? Who knows? But if Gerry Manheim, Account Executive, has to print out his weekly expense report as a part of his job, you better believe print preview needs to be in there. There’s nothing magical here; as always, it boils down to knowing who your users are and what they really do – and the personas technique is a great way to get there.

There’s also an interesting analysis here of how developers tend to think themselves qualified to make usability decisions on behalf of “regular” users, when in reality they’re anything but. Developers are freakish, extreme users at best– “Homo Logicus” versus “Homo Sapiens.” Unless you happen to be writing a compiler where developers are the end users.

One hidden lesson in this book is that sometimes it doesn’t matter how good your design is: the scanner software and the web development software which Alan consulted on, and uses as examples in this book, both failed in the marketplace for reasons that had nothing to do with their usability– which was verifiably excellent.* Sometimes great products fail for reasons beyond your control, no matter how hard you try. Feel free to use this fact to counterbalance the sometimes bombastic tone of the book.

* I owned the exact model of “behind the keyboard” USB scanner pictured in the book, and I was quite impressed with the bundled scanning software. I eventually gave this scanner to my Dad. One time I was chatting on the phone with him and without any prompting at all, he mentioned to me how much he liked the scanning software. This was before the book had been published!

Programming Pearls


I hesitated to include Programming Pearls because it covers some fairly low-level coding techniques, but there are enough “pearls” of software craftsmanship embedded in this book to make it well worth any developer’s time. Any book containing this graph..

.. is worth its weight in gold. TRS-80 versus DEC Alpha to illustrate 48n versus n3 algorithms? Come on folks, it just doesn’t get any better than that. Programming Pearls is the next best thing to working side by side with a master programmer for a year or so. It is the collective wisdom of many journeyman coders distilled into succinct, digestible columns.

I won’t lie to you: there are entire chapters that can probably be ignored. For example, I can’t imagine implementing sorting, heap, or hash algorithms as documented in columns 11, 13, and 14 respectively, given today’s mature libraries of such basic primitives. But for every textbook-tedious exercise, there is real, practical advice alongside. Just scan through the book, ignoring the code sections, and I doubt you’ll be disappointed. Column 8, “Back of the Envelope” is essential, probably the best treatment of estimation I’ve seen anywhere. It also goes a long way towards explaining those crazy interview questions that companies love to annoy us with.
You can read sample sections of the book online if you’re still on the fence. I recently used the chapter on strings to illustrate the use of Markov chains in generating synthetic data to fill an empty database with – a performance estimation technique covered in “Back of the Envelope”.

The Pragmatic Programmer: From Journeyman to Master


This book reminds me a lot of Programming Pearls, but it’s actually better, because it’s less focused on code. Instead of worrying about code, the authors boiled down all the practical approaches that they’ve found to work in the real world into this one book. Not all of these things are technically programming. For example, asking yourself “why am I doing this? Is this even worth doing at all?” isn’t thinking outside the box; it’s something you should incorporate into your daily routine to keep yourself – and your co-workers – sane. And that’s what makes Pragmatic Programmer such a great book.

If you’d like to know a little more about the book, I created a HTML version of the pullout reference card included inside, which provides a nice overview of the contents.

Designing Web Usability


Jakob Neilsen is well known for his usability site, and his career as a usability expert extends back to 1989 when his first book was published. Designing Web Usability is of course a full-on web usability primer, so it’s a bit different than the GUI-oriented Cooper books.

The Visual Display of Quantitative Information


Visual Explanations: Images and Quantities, Evidence and Narrative


Envisioning Information


Beautiful Evidence



Information is beautiful. And so is a well-designed GUI.

You don’t need to own all four books in the series unless you’re a completist (or a masochist, I suppose), but the first two are essential.

Chris Sells has some interesting insight on the Tufte books based on a Tufte seminar he attended in June 2004.

Regular Expressions Cookbook


UNIX has a well-deserved reputation for being complex and impenetrable. So do Regular Expressions.

I may be a card carrying member of the “Keep It Simple Stupid” club, but I’m making a meteor sized exception for regular expressions. Written properly, they will save you a tremendous amount of time in string manipulation, and I’ve never run across a project where they didn’t come in handy somewhere.

Once you delve into the world of regular expressions, you may become drunk with the amazing power and potential they have, which results in things like Perl. Remember, absolute power corrupts absolutely. But it also rocks absolutely.

5 insanely great books about mathematics you should read

Kelly J. Rose

Source: https://wp.kjro.se/2013/12/27/5-insanely-great-books-about-mathematics-you-should-read/

I’ve been asked over and over for good books about mathematics for a layperson, someone who hasn’t taken advanced courses in university and is more simply interested in learning about what math is, and some of the more interesting historical figures and results from mathematics. Ironically, when you are a mathematics major at Waterloo, you get the opportunity in 4th year to take a course on the history of mathematics and you get introduced to a few really good books that start to explain the mindset and philosophy behind mathematics and not simply just the theorems and proofs.

Here are the 5 books about I most recommend to those who want to understand the mathematical mind and philosophy.

Boyer's a History of Mathematics

Boyer’s a History of Mathematics

A History of Mathematics,
Carl B. Boyer

This is the textbook from the History of Mathematics course I took almost a decade ago now, and it is still one of the best and most thorough discussions of how mathematics developed over the past millenia. It starts in with Egyptian and pre-classical mathematics, explaining how simple tasks were complicated by a lack of mathematical tools and then how over time different tools were developed that led to quantum leaps in our understanding of the field. It’s quite a tome, with over 700 pages of details, but it is fully accessible to the non-technical reader.

This is well worth having in any library and it can be read in chunks as each chapter covers a different aspect of mathematical history.

Journeys Through Genius

Journeys Through Genius

Journey Through Genius,
William Dunham

I picked up this book at a secondhand store many years back simply because it caught my attention and was a good price. I thought it would be an enjoyable read, but I never expected to be as amazed and excited by the contents as I started to dig through it. This book takes some of the most important and paradigm-shifting theorems of mathematics and explains them in a clear and accessible fashion. Historical artifacts around the development of the theorems are displayed in a fun and pleasing fashion, keeping the importance of the discovery in context with the time. As well, most importantly, beyond explaining the theorems, the characters behind the work as shown and their lives are taken into context with the immensity of their work. This is a beautiful read and worth picking up if you want to learn more about the biggest theorems in mathematics.

The Mathematical ExperienceThe Mathematical Experience,
Philip J. David, Reuben Hersh

My professor for the history of mathematics course lent me his copy of this book and it was probably one of the most eye-opening reads I’ve ever had. I spent an entire weekend reading it cover-to-cover and then re-reading it again, devouring and absorbing all of the ideas and concepts within it.

Without a doubt, this is the best book I’ve got on my library from the perspective of discussion what it means to be a mathematician and the experience shared by mathematicians worldwide. This book covers the entire gamut, from the philosophical to the social-emotional experience of a mathematician. It is well-written, concise and strikes a real chord with me. In this book I really felt that I was reading someone who got what it meant to love mathematics and get excited by it without delving really deep into difficult to process material. If there is one book on this entire list that I recommend going and purchasing right now, it is this one.

Go, buy it now!

Proofs from the Book

Proofs from the Book

Proofs from the Book,
Martin Aigner, Günter M. Ziegler

Paul Erdös, one of the most prolific mathematicians of the 20th century would commonly refer to a proof that was singularly beautiful as being “from the book.” As in, “from the book of God himself.” This book is a collection of some of the proofs that many mathematicians think to be essential and important, while still be uniquely beautiful in their elegance. If you want a book which is still accessible, but allows for exploration of the theorems themselves in am ore rigourous fashion, this is the book for you. It’s clean and covers some of the best proofs in a very wide variety of fields.

Proofs and Refutations

Proofs and Refutations

Proofs and Refutations,
Imre Lakatos

This books is probably the most advanced of the books on this list. It is however brilliantly written in the form of a discussion between a professor and their students. Lakatos weaves in and out over the process of mathematics, covering how mathematics is really done and evolves as theorems adapt based on a variety of very easy to understand techniques.

If you, or anyone you know, is actually considering to go into mathematics as a profession, I would recommend reading this book. This especially includes teachers as it explains how working through the technique and philosophy can help with overall understanding and creative use of the new tools learned as you move forward. This is a truly wonderful book and can be a very quick read.



2016-02-10 方军 做書







 01 《网络经济的十种策略》

凯文·凯利(Kevin Kelly, KK),广州出版社,2000年





 02 《创业维艰:如何完成比难更难的事》






 03 《麦哲伦传》






 04 《一代新机器的灵魂》





我们创造的多数是网站、APP、商业系统,但是,所经历的过程是一样的。其实这本书和迈克尔·刘易斯记录早期互联网创业的《将世界甩在背后》(The New New Thing)争夺一个清单推荐位,而最终选择了《机器》,因为读它的过程很多感慨,而《世界》并没有。

 05 《黑客与画家:硅谷创业之父Paul Graham文集》

Paul Graham/著,人民邮电出版社,2011年


YC创业营的创办人Paul Graham已经变成一种象征,推荐这本书实际上并非仅仅推荐这本书,因为这本书是完结不变的,而他还在不断地写作长文(essay),讲述他的思考,值得持续关注。

比如他最近有一篇新文章讨论的是“Life is short”,他讨论的这个问题,他的答案隐藏在题目中:“从问题的终极反过来看,去培养一种对你想做的事迫不及待的急躁习惯。”


 06 《精益创业:新创企业的成长思维》




 07 《创业必经的那些事》







 08 《启示录:打造用户喜欢的产品》

Marty Cagan/著,华中科技大学出版社,2011年



 09 《四步创业法》

Steven Blank/著,华中科技大学出版社,2012年


仔细读过《精益创业》的都了解这本名为《The Four Steps to the Epiphany》的书,它是《精益创业》的灵感之源,埃里克·莱斯说他送了很多箱出去。


 10 《大决策:九个不朽的领导力传奇故事》





 11 《丰田汽车案例:精益制造的14项管理原则》


“丰田模式可以扼要地总结为两大支柱:一为“持续改进”(continuous Improvement),二为“尊重员工”(respect for people)。






 12 《跨越鸿沟:颠覆性产品营销圣经》



这就是提出技术产品接纳周期曲线、指出这条曲线里的 “鸿沟”(Chasm )的那个杰弗里·摩尔最早的作品之一。


 13 《创新者的窘境》



这就是时下热门的“颠覆式创新” (disruptive creation,破坏式创新)的原典,最早读夹杂在汉译大众精品文库中这本时,做了非常多笔记,尤其对克里斯坦森对理论和现实的看法感兴趣,在当面向他请教时提了很多问题,但现在已经完全不记得那一个多小时问了什么,只依稀记得讨论linux、google docs等等。


 14 《企业参谋》




 15 《创业之初你不可不知的融资知识》





 16 《错不在我?》
卡罗尔·塔夫里斯、艾略特·阿伦森/著, 中信出版社,2013年

“在有意识撒谎欺骗他人与下意识地自我辩护欺骗自己之间,有一块被不可靠、自利的记忆掌握的灰色地带。记忆通常都会受自我提升偏误(self-enhancing bias)修正和改变,让过去发生的事情变得模糊,减轻责难,扭曲事实的真相。”



 17 《创业无畏:指数级成长路线图》








 18 《九败一胜:美团创始人王兴创业十年》



原来的美团,已经合并大众点评变成新美大(据说英文名为China Internet Plus),但它还在奋战。


 19 《深度生存:生还是死难?》




 20 《卓有成效的管理者》




与之相似的,英特尔的格鲁夫也有一本平淡无奇的书《格鲁夫给经理人的第一课》(high output management),他相对更关注系统的高效率一些,也值得推荐。


程序员必读书单 1.0





Reading makes a full man; conference a ready man; and writing an exact man.

Francis Bacon


  • 良好的程序设计能力:
    • 掌握常用的数据结构和算法(例如链表,栈,堆,队列,排序和散列);
    • 理解计算机科学的核心概念(例如计算机系统结构、操作系统、编译原理和计算机网络);
    • 熟悉至少两门以上编程语言(例如C++,Java,C#,和Python);
  • 专业的软件开发素养:
    • 具备良好的编程实践,能够编写可测试(Testable),可扩展(Extensible),可维护(Maintainable)的代码;
    • 把握客户需求,按时交付客户所需要的软件产品;
    • 理解现代软件开发过程中的核心概念(例如面向对象程序设计,测试驱动开发,持续集成,和持续交付等等)。



  • 经典书籍需要不断被重读——每一次重读都会有新的体会;
  • 书籍并非读的越多越好——大多数书籍只是经典书籍中的概念延伸(有时甚至是照搬);


  • 优秀的程序员应该掌握哪些关键概念?
  • 哪些书籍来可以帮助程序员掌握这些关键概念?





  1. 必读:什么是必读书籍呢?如果学习某项技术有一本书无论如何都不能错过,那么这本书就是必读书籍——例如Effective Java于Java,CLR via C#于C#;
    • 注意我没有使用“经典”这个词,因为经典计算机书籍往往和计算机科学联系在一起,而且经典往往需要10年甚至更长的时间进行考验;
  2. 注重实践,而非理论:所以这个书单不会包含过于原理性的书籍;
  3. 入门—必读—延伸:必读书籍的问题在于:1. 大多不适合入门;2. 不够全面。考虑到没有入门阅读和延伸阅读的阅读列表是不完整的——所以书单中每个关键概念都会由一本入门书籍,一本必读书籍(有时入门书籍和必读书籍是同一本),和若干延伸阅读书籍所构成。


  1. 全面:全面覆盖软件开发中重要的概念;
  2. 通用:适用于每一个程序员,和领域特定方向无关;
  3. 注重基础,但不过于深入:优秀的程序员需要良好的计算机科学基础,但程序员并没必要掌握过于深入的计算机科学知识。以算法为例,每个程序员都应该掌握排序、链表、栈以及队列这些基本数据结构和算法,但计算几何、线性规划和网络流这些算法可能就不是每个程序员都需要掌握的了;



自从开博以来,经常会有朋友在论坛,微博,和QQ上提问学习X技术读什么书合适(例如:学习Java读什么书合适?如何学习程序设计?)所以我在这 里列出了一个“快速通道”——把常见的问题集中在一起,点击问题,即可直接进入答案。(当然,如果你把本文从头读到尾帮助会更大 :–))




  1. 基础理论编码:隐匿在计算机软硬件背后的语言
  2. 编程语言
  3. 编程语言理论编程语言实现模式
  4. 程序设计程序设计方法
  5. 算法与数据结构算法(第4版)
  6. 程序调试调试九法——软硬件错误的排查之道


  1. 编程实践程序设计实践
  2. 面向对象程序设计Head First设计模式
  3. 重构重构
  4. 软件测试How to Break Software
  5. 项目管理极客与团队
  6. 专业开发程序员修炼之道:从小工到专家
  7. 大师之言奇思妙想:15位计算机天才及其重大发现
  8. 界面设计写给大家看的设计书
  9. 交互设计通用设计法则


  1. 职业规划软件开发者路线图
  2. 思维方式程序员的思维修炼:开发认知潜能的九堂课
  3. 求职面试金领简历:敲开苹果微软谷歌的大门
  4. 英语写作The Only Grammar Book You’ll Ever Need



  1. 基础理论深入理解计算机系统(第2版)
  2. 编程语言
  3. 编程语言理论程序设计语言——实践之路(第3版)
  4. 程序设计计算机程序的构造与解释(第2版)
  5. 算法与数据结构编程珠玑(第2版)
  6. 程序调试调试九法——软硬件错误的排查之道


  1. 编程实践代码大全(第2版)
  2. 面向对象程序设计设计模式
  3. 重构修改代码的艺术
  4. 软件测试xUnit Test Patterns
  5. 项目管理人月神话
  6. 专业开发程序员职业素养
  7. 大师之言编程人生:15位软件先驱访谈录
  8. 界面设计认知与设计:理解UI设计准则(第2版)
  9. 交互设计交互设计精髓(第3版)


  1. 职业规划软件开发者路线图
  2. 思维方式如何把事情做到最好
  3. 求职面试程序员面试金典(第5版)
  4. 英语写作风格的要素


  • 基础理论包括了程序员应该掌握的计算机基础知识;
  • 编程语言对软件开发至关重要,我选择了CC++JavaC#Python,和JavaScript这六门主流编程语言进行介绍,如果想进一步理解编程语言,可以阅读编程语言理论里的书目;
  • 在理解编程语言的基础上,优秀的程序员还应该了解各种程序设计技巧,熟悉基本的算法数据结构,并且能够高效的进行程序调试
  • 良好的程序设计能力是成为优秀程序员的前提,但软件开发知识也是必不可少的:优秀的程序员应具备良好的编程实践,知道如何利用面向对象重构,和软件测试编写可复用,可扩展,可维护的代码,并具备软件项目管理知识和专业开发素养;
  • 就像我们可以从名人传记里学习名人的成功经验,程序员也可以通过追随优秀程序员的足迹使自己少走弯路。大师之言包含一系列对大师程序员/计算机科学家的访谈,任何程序员都可以从中获益良多;
  • 为了打造用户满意的软件产品,程序员应当掌握一定的界面设计知识和交互设计知识(是的,这些工作应该交给UI和UX,但如果你想独自打造一个产品呢?);
  • 专业程序员应当对自己进行职业规划,并熟悉程序员求职面试的流程,以便在职业道路上越走越远;
  • 软件开发是一项需要不断学习的技能,学习思维方式可以有效的提升学习能力和学习效率;
  • 软件开发是一项国际化的工作,为了让更多的人了解你的代码(工作),良好的英语写作能力必不可少。



1. 基础理论


编码:隐匿在计算机软硬件背后的语言这本书其实不应该叫编码——它更应该叫“Petzold教你造计算机”——作者Charles Petzold创造性的以编码为主题,从电报机和手电筒讲到数字电路,然后利用数字电路中的逻辑门构造出加法器触发器,最后构造出一个完整的存储程序计算机。不要被这些电路概念吓到——编码使用大量形象贴切的类比简化了这些概念,使其成为最精彩最通俗易懂的计算机入门读物。


深入理解计算机系统(第2版)这本书的全名是:Computer Systems:A Programmer’s Perspective(所以它又被称为CSAPP),我个人习惯把它翻译为程序员所需了解的计算机系统知识,尽管土了些,但更名副其实。



2. 编程语言


需要注意的是:我在这里给出的是编程语言(Programming Language)书籍,而非编程平台(Programming Platform)书籍。以Java为例,Effective Java属于编程语言书籍,而Android编程权威指南就属于编程平台书籍。








  • C专家编程:不要被标题中的“专家”吓到,这实际是一本很轻松的书籍,它既包含了大量C语言技术细节和编程技巧,也包含了很多有趣的编程轶事;
  • C陷阱与缺陷:书如其名,这本书介绍了C语言中常见的坑和一些稀奇古怪的编程“技巧”,不少刁钻的C语言面试题都源自这本小册子;
  • C语言参考手册:全面且权威的C语言参考手册,而且覆盖C99,如果你打算成为C语言专家,那么这本书不可错过;
  • C标准库:给出了15个C标准库的设计思路,实现代码,以及测试代码,配合C程序设计语言阅读效果更佳;
  • C语言接口与实现:这本书展示了如何使用C语言实现可复用的数据结构,其中包含大量C语言高级技巧,以至于Amazon上排行第一的评论是“Probably the best advanced C book in existance”,而排行第二的评论则是“By far the most advanced C book I read”。



作为C++的发明者,没有人能比Bjarne Stroustrup更理解C++。Bjarne在Texas A&M大学任教时使用C++为大学新生讲授编程,从而就有了C++程序设计原理与实践这本书——它面向编程初学者,既包含C++教程,也包含大量程序设计原则。它不但是我读过最好的C++入门书,也是我读过最好的编程入门书。



同样是Bjarne Stroustrup的作品,C++程序设计语言是C++最权威且最全面的书籍。第4版相对于之前的版本进行了全面的更新,覆盖了第二新的C++ 11标准,并砍掉了部分过时的内容。


  • A Tour of C++:如果你觉得C++程序设计语言过于庞大,但你又想快速的浏览一遍新版C++的语言特色,那么可以试试这本小红书;
  • C++语言的设计与演化:C++的“历史书”,讲述了C++是如何一步一步从C with Classes走到如今这一步,以及C++语言特性背后的故事;
  • C++标准库(第2版):相对于其它语言的标准库,C++标准库虽然强大,但学习曲线十分陡峭,这本书是学习C++标准库有力的补充;
  • 深度探索C++对象模型:这本书系统的讲解了C++是如何以最小的性能代价实现对象模型,很多C++面试题(包括被问烂的虚函数指针)都可以在这本书里找到答案;
  • Effective C++More Effective C++:由于C++的特性实在繁杂,因此很容易就掉到坑里。Effective系列既讲述了C++的良好编程实践,也包含C++的使用误区,从而帮你绕过这些坑。



平心而论Java核心技术(即Core Java)并不算是一本特别出色的书籍:示例代码不够严谨,充斥着很多与C/C++的比较,语言也不够简洁——问题在于Java并没有一本很出色的入门书籍,与同类型的Java编程思想相比,Java核心技术至少做到了废话不多,与时俱进(Java编程思想还停留在Java 6之前),矮子里面选将军,Java核心技术算不错了。

Effective Java(第2版)

尽管Java没有什么出色的入门书籍,但这不代表Java没有出色的必读书籍。Effective Java是我读过的最好的编程书籍之一,它包含大量的优秀Java编程实践,并对泛型和并发这两个充满陷阱的Java特性给出了充满洞察力的建议,以至于Java之父James Gosling为这本书作序:“我很希望10年前就拥有这本书。可能有人认为我不需要任何Java方面的书籍,但是我需要这本书。”


  • 深入理解Java虚拟机(第2版):非常优秀且难得的国产佳作,系统的介绍了Java虚拟机和相关工具,并给出了一些调优建议;
  • Java程序员修炼之道:在这本书之前,并没有一本Java书籍系统详细的介绍Java 7的新特性(例如新的垃圾收集器,try using结构和invokedynamic指令),这本书填补了这个空白;
  • Java并发编程实践:系统全面的介绍了Java的并发,如何设计支持并发的数据结构,以及如何编写正确的并发程序;
  • Java Puzzlers:包含了大量的Java陷阱——以至于读这本书时我说的最多的一个词就是WTF,这本书的意义在于它是一个反模式大全,Effective Java告诉你如何写好的Java程序,而Java Puzzlers则告诉你糟糕的Java程序是什么样子。更有意思的是,这两本书的作者都是Joshua Bloch


  • Java语言学习极速之旅:系统全面的Java语言教程,6个阶段Java基础入门,循序渐进掌握Java面向对象精髓。3个Java进阶方向,Java SE、Java EE、Android开发,每一个都包含相应的知识点精讲和项目开发实例,快速上手。
  • Android 0基础极速养成计划:Android开发快速入门视频教程,通过对Android基础知识讲解,详细介绍Android开发环境搭建,同时包含Android实战案例解析,通过全新实战的Android课程,系统学习Android开发。




  1. C#的语言特性非常丰富,很难用简短的篇幅概括这些特性;
  2. 精通C#之所以有近1200页的篇幅,是因为它不但全面介绍了C#语言,而且还覆盖了ADO.NET,WCF,WF,WPF,以及ASP.NET这些.Net框架。你可以把这本书视为两本书——一本500多页的C#语言教程和一本600多页的.Net平台框架快速上手手册。
  3. 尽管标题带有“精通”两字,精通C#实际上是一本面向初学者的C#书籍,你甚至不需要太多编程知识,就可以读懂它。

CLR via C#(第4版)

CLR via C#是C#/.Net最重要的书籍,没有之一。它全面介绍了.Net的基石——CLR的运行原理,以及构建于CLR之上的C#类型系统,运行时关系,泛型,以及线程/并行等高级内容。任何一个以C#为工作内容的程序员都应该阅读此书。


  • 深入理解C#(第3版):C#进阶必读,这本书偏重于C#的语言特性,它系统的介绍了C#从1.0到C# 4.0的语言特性演化,并展示了如何利用C#的语言特性编写优雅的程序;
  • .NET设计规范(第2版):C#专业程序员必读,从变量命名规范讲到类型系统设计原则,这本书提供了一套完整的.Net编程规范,使得程序员可以编写出一致,严谨的代码,
  • C# 5.0权威指南:来自O’Reilly的C#参考手册,严谨的介绍了C#语法,使用,以及核心类库,C#程序员案头必备;
  • LINQ to Objects Using C# 4.0Async in C# 5.0:LINQ和async分别是.Net 3.5和.Net 4.5中所引入的最重要的语言特性,所以我认为有必要在它们上面花点功夫——这两本书是介绍LINQ和async编程的最佳读物。


JavaScript DOM编程艺术(第2版)

尽管JavaScript现在可以做到客户端服务器端通吃,尽管JQuery之类的前端框架使得一些人可以不懂JavaScript也可以编程,但我还是认为学习JavaScript从HTML DOM开始最为适合,因为这是JavaScript设计的初衷。JavaScript DOM编程艺术系统的介绍了如何使用JavaScript,HTML,以及CSS创建可用的Web页面,是一本前端入门佳作。


JavaScript语言包含大量的陷阱和误区,但它却又有一些相当不错的特性,这也是为什么Douglas Crockford称JavaScript为世界上最被误解的语言,并编写了JavaScript语言精粹一书来帮助前端开发者绕开JavaScript中的陷阱。和同类书籍不同,JavaScript语言精粹用精炼的语言讲解了JavaScript语言中好的那部分(例如闭包,函数是头等对象,以及对象字面量),并建议读者不要使用其它不好的部分(例如混乱的类型转换,默认全局命名空间,以及奇葩的相等判断符),毕竟,用糟糕的特性编写出来的程序往往也是糟糕的。







权威且实用的Python书籍,覆盖Python 2和Python 3。尽管它名为参考手册,但Python参考手册在Python语法和标准库基础之上对其实现机制也给出了深入的讲解,不容错过。


3. 编程语言理论


大多数程序员并不需要从头编写一个编译器或解释器,因此龙书(编译原理)就显得过于重量级;然而多数程序员还是需要解析文本,处理配置文件,或者写一个小语言,编程语言实现模式很好的满足了这个需求。它把常用的文本解析/代码生成方法组织成一个个模式,并为每个模式给出了实例和应用场景。这本书既会提高你的动手能力,也会加深你对编程语言的理解。Python发明者Guido van Rossum甚至为这本书给出了“Throw away your compiler theory book!”这样的超高评价。




  • 七周七语言:理解多种编程范型:尽管我们在日常工作中可能只使用两三门编程语言,但是了解其它编程语言范式是很重要的。七周七语言一书用精简的篇幅介绍了Ruby,Io,Prolog,Scala,Erlang,Clojure,和Haskell这七种具有不同编程范式的语言——是的,你没法通过这本书变成这七种语言的专家,但你的视野会得到极大的拓宽;
  • 自制编程语言:另一本优秀的编译原理作品,自制编程语言通过从零开始制作一门无类型语言Crowbar和一门静态类型语言Diksam,把类型系统,垃圾回收,和代码生成等编程语言的关键概念讲的清清楚楚;
  • 计算的本质:深入剖析程序和计算机:披着Ruby外衣的计算理论入门书籍,使你对编程语言的理解更上一层楼。

4. 程序设计





计算机程序的构造与解释是另一本被国内大学忽视(至少在我本科时很少有人知道这本书)的教材,这本书和程序设计方法有很多共同点——都使用Scheme)作为教学语言;都专注于程序设计方法而非编程语言本身;都拥有相当出色的课后题。相对于程序设计方法计算机程序的构造与解释要更加深入程序设计的本质(过程抽象,数据抽象,以及元语言抽象),以至于Google技术总监Peter Norvig给了这本书超高的评价


  • 编程原本STL作者的关于程序设计方法佳作——他把关系代数和群论引入编程之中,试图为程序设计提供一个坚实的理论基础,从而构建出更加稳固的软件。这本书是程序设计方法计算机程序的构造与解释的绝好补充——前者使用函数式语言(Scheme)讲授程序设计,而编程原本则使用命令式语言(C++);
  • 元素模式设计模式总结了面向对象程序设计中的模式,而元素模式这本书分析了程序设计中的常见模式的本质,阅读这本书会让你对程序设计有更深的理解;
  • The Science of Programming:会编程的人很多,但能够编写正确程序的人就少多了。The Science of Programming通过前条件——不变式——后条件以及逻辑谓词演算,为编写正确程序提供了强有力的理论基础,然后这本书通过实例阐述了如何应用这些理论到具体程序上。任何一个想大幅提高开发效率的程序员都应阅读此书。

5. 算法与数据结构



  • 使用更为容易的Java语言作为教学语言;
  • 覆盖所有常用的数据结构和算法,并均给出其完整实现;
  • 包含大量的图示用于可视化算法——事实上这是我读过的图示最为丰富形象的书籍,这也是我称其为最好的算法入门书籍的原因。


编程珠玑(第2版)是一本少见的实践型算法书籍——它并非一一介绍数据结构/算法的教材,而是实践性极强的算法应用手册。作者(Jon Bentley)从他多年的实际经验精选出一些有趣而又实用的问题,然后展示了他解决这些问题的过程(分析问题,选择合适的算法,解决问题,以及验证答案)。任何程序员都可以从中获益。


  • 编程珠玑(续):严格来说这本书并非编程珠玑的续作,而是一本类似于番外篇的编程技巧/实践手册;它不像编程珠玑那般重视算法的应用,而是全面覆盖了程序员所需的能力;
  • 算法导论(第3版):尽管我在这边文章开头提到会尽量避免理论性的书籍,但没有算法导论的算法阅读列表是不完整的,我想这本书就不需要我多介绍了; :–)
  • 算法设计与分析基础(第3版):侧重于算法设计,这本书创新的把常见算法分为分治,减治,变治三大类,并覆盖了动态规划,回溯,以及分支定界等高级算法设计方法,属于算法设计的入门佳作;

6. 程序调试




  • Writing Solid Code最好的调试是不调试——Writing Solid Code介绍了断言,设计清晰的API,以及单步代码等技巧,用于编写健壮的代码,减少调试的时间;
  • 软件调试的艺术:调试工具书——这本书详细的介绍了常见的调试器工具,并通过具体案例展示了它们的使用技巧;


1. 编程实践


Brian Kernighan是这个星球上最好的计算机书籍作者:从上古时期的Software Tools,到早期的Unix编程环境C程序设计语言,再到这本程序设计实践,每本书都是必读之作。



无论在哪个版本的程序员必读书单,代码大全都会高居首位。和其它程序设计书籍不同,代码大全用通俗清晰的语言覆盖了软件构建(Software Construction)中各个层次上所有的重要概念——从变量命名到类型设计,从控制循环到代码结构,从测试和调试到构建和集成,代码大全可谓无所不包,你可以把这本书看作为程序员的一站式(Once and for all)阅读手册。更珍贵的是,代码大全在每一章末尾都给出了价值很高的参考书目(参考我之前的如何阅读书籍一文),如果你是一个初出茅庐的程序员,代码大全是绝好的阅读起点。


  • 编写可读代码的艺术:专注于代码可读性(Code Readability),这本书来自Google的两位工程师对Google Code Readability的总结。它给出了大量命名,注释,代码结构,以及API设计等日常编码的最佳实践,并包含了很多看似细微但却可以显著提升代码可读性的编程技巧。这本书的翻译还不错,但如果你想体会书中的英语幽默(例如Tyrannosaurus——Stegosaurus——Thesaurus),建议阅读它的英文影印版
  • 卓有成效的程序员:专注于生产效率(Productivity),它既包含源自作者多年经验的高生产率原则,也包含大量的提高生产率的小工具,每个追求高生产率的程序员都应该阅读这本书;
  • UNIX编程艺术:专注于程序设计哲学,这本书首先总结出包括模块化,清晰化,可组合,可分离等17个Unix程序设计哲学,接下来通过Unix历史以及各种Unix编程工具展示了这些原则的应用。尽管个人觉的这本书有些过度拔高Unix且过度贬低Windows和M$,但书中的Unix设计哲学非常值得借鉴。

2. 面向对象程序设计

Head First设计模式

无论是在Amazon还是在Google上搜索设计模式相关书籍,Head First设计模式都会排在首位——它使用风趣的语言和诙谐的图示讲述了观察者,装饰者,抽象工厂,和单例等关键设计模式,使得初学者可以迅速的理解并掌握设计模式。Head First设计模式在Amazon上好评如潮,就连设计模式原书作者Erich Gamma都对它给出了很高的评价。

需要注意,Head First设计模式是非常好的设计模式入门书,但千万不要把这本书作为学习设计模式的唯一的书——是的,Head First设计模式拥有风趣的语言和诙谐的例子,但它既缺乏实际的工程范例,也没有给出设计模式的应用/适用场景。我个人建议是在读过这本书之后立即阅读“四人帮”)的设计模式Bob大叔敏捷软件开发,以便理解设计模式在实际中的应用。


设计模式作为设计模式领域的开山之作,Erich Gamma,Richard Helm,Ralph Johnson等四位作者将各个领域面向对象程序开发的经验总结成三大类23种模式,并给出了每个模式的使用场景,变体,不足,以及如何克服这些不足。这本书行文严谨紧凑(四位作者都是PhD),并且代码源自实际项目,属于设计模式领域的必读之作。



3. 重构



我见过很多程序员,他们经常声称自己在重构代码,但他们实际只做了第二步(提升代码的质量),却没有保证第一步(保持代码行为),因此他们所谓的重构往往会适得其反——破坏现有代码或是引入新bug。这也是我推荐重构这本书的原因——它既介绍糟糕代码的特征(Bad smell)和改进代码的方法,也给出了重构的完整流程——1. 编写单元测试保持(Preserve)程序行为;2. 重构代码;3. 保证单元测试通过。重构还引入了一套重构术语(诸如封装字段,内联方法,和字段上移),以便程序员之间交流。只有理解了这三个方面,才能算是理解重构。



提升代码质量并不困难,但保持代码行为就难多了,尤其是对没有测试的遗留代码(Legacy Code)而言——你需要首先引入测试,但遗留代码往往可测试性(Testability)很差,这时你就需要把代码变的可测试。修改代码的艺术包含大量的实用建议,用来把代码变的可测试(Testable),从而使重构变为可能,使提高代码质量变为可能。


  • 重构与模式:这本书的中文书名存在误导,它的原书书名是Refactoring to Patterns——通过重构,把模式引入代码。这本书阐述了重构和设计模式之间的关系,使得程序员可以在更高的层次上思考重构,进行重构。

4. 软件测试

How to Break Software

关于软件测试的书籍很多,但很少有一本测试书籍能像How to Break Software这般既有趣又实用。不同于传统的软件测试书籍(往往空话连篇,无法直接应用),How to Break Software非常实际——它从程序员的心理出发,分析软件错误/Bug最可能产生的路径,然后针对这些路径进行残酷的测试,以保证软件质量。


注意:如果你是一个测试工程师,那么在阅读这本书前请三思——因为阅读它之后你会让你身边的程序员苦不堪言,甚至连掐死你的心都有 :-D。

xUnit Test Patterns

How to Break Software注重黑盒测试,而这本xUnit Test Patterns则注重白盒测试。正如书名所示,xUnit Test Patterns覆盖了单元测试的每个方面:从如何编写良好的单元测试,到如何设计可测试(Testable)的软件,再到如何重构测试——可以把它看作为单元测试的百科全书。


  • Practical Unit Testing with JUnit and Mockito:尽管xUnit Test Patterns覆盖了单元测试的方方面面,但它的问题在于不够与时俱进(07年出版)。Practical Unit Testing弥补了这个缺陷——它详细介绍了如何通过测试框架JUnit和Mock框架Mockito编写良好的单元测试,并给出了大量优秀单元测试的原则;
  • 单元测试的艺术(第2版):可以把这本书看作为前一本书的.Net版,适合.Net程序员;
  • Google软件测试之道:这本书详细介绍了Google如何测试软件——包括Google的软件测试流程以及Google软件测试工程师的日常工作/职业发展。需要注意的是:这本书中的测试流程在国内很可能行不通(国内企业缺乏像Google那般强大的基础设施(Infrastructure)),但它至少可以让国内企业有一个可以效仿的目标;
  • 探索式软件测试James Whittaker的另一本测试著作,不同于传统的黑盒/白盒测试,这本书创造性的把测试比喻为“探索”(Exploration),然后把不同的探索方式对应到不同的测试方式上,以便尽早发现更多的软件错误/Bug。

5. 项目管理


很多程序员都向往成为横扫千军(One-man Army)式的“编程英雄”,但卓越的软件并非一人之力,而是由团队合力而成。极客与团队就是这样一本写给程序员的如何在团队中工作的绝好书籍,它围绕着HRT三大原则(Humility谦逊,Respect尊重,和Trust信任),系统的介绍了如何融入团队,如何打造优秀的团队,如何领导团队,以及如何应对团队中的害群之马(Poisonous People)。这本书实用性极强,以至于Python之父Guido van Rossum都盛赞这本书“说出了我一直在做但总结不出来的东西”


尽管人月神话成书于40年前,但它仍是软件项目管理重要的书籍。人月神话源自作者Fred Brooks领导并完成System/360OS/360这两个即是放到现在也是巨型软件项目的里程碑项目的经验总结。它覆盖了软件项目各个方面的关键概念:从工期管理(Brooks定律)到团队建设(外科团队),从程序设计(编程的本质是使用正确的数据结构)到架构设计(概念完整性),从原型设计(Plan to Throw one away)到团队交流(形式化文档+会议)。令人惊讶的是,即便40年之后,人月神话中的关键概念(包括焦油坑,Brooks定律概念完整性外科团队第二版效应等等)依然适用,而软件开发的核心复杂度仍然没有得到解决(没有银弹)。


  • 人件(原书第3版):从人的角度分析软件项目。人件从雇佣正确的人,创建健康的工作环境,以及打造高效的开发团队等角度阐述了如何改善人,从而改善软件项目;
  • 门后的秘密:卓越管理的故事:这本书生动的再现了软件项目管理工作的场景,并给出了各种实用管理技巧,如果你有意转向管理岗位,这本书不容错过;
  • 大教堂与集市:这本书从黑客的历史说起,系统而又风趣的讲述了开源运动的理论和实践,以及开源软件项目是如何运作并发展的。了解开源,从这本书开始。

6. 专业开发




程序员修炼之道指出了如何成为专业程序员,这本程序员职业素养则指出了专业程序员应该是什么样子——承担责任;知道自己在做什么;知道何时说不/何时说是;在正确的时间编写正确的代码;懂得自我时间管理和工期预估;知道如何应对压力。如果你想成为专业程序员(Professional Developer)(而不是码农(Code Monkey)),这本书会为你指明前进的方向。


7. 大师之言





同样是访谈录,同样访谈15个人,编程人生把重点放在程序员(Coders at work)上。它从各个领域选取了15位顶尖的程序员,这些程序员既包括Ken ThompsonJamie Zawinski这些老牌Unix黑客,也包括Brad Fitzpatrick这样的80后新生代,还包括Frances AllenDonald Knuth这样的计算机科学家。这种多样性(Diversity)使得编程人生兼具严谨性和趣味性,无论你是什么类型的程序员,都能从中受益良多。


  • 图灵和ACM图灵奖(1966-2011):通过图灵奖介绍整个计算机科学发展史,非常难得的国产精品图书;
  • 编程大师访谈录:可以把这本书看作为二十年前的编程人生,被访谈者都是当时叱咤风云的人物(例如微软的创造者Bill Gates,Macintosh的发明者Jeff Raskin,以及Adobe的创始人John Warnock等等)。有趣的是这本书中大量的经验和建议到如今依然适用;
  • 编程大师智慧:类似于编程人生,不同的是被访谈者都是编程语言的设计者——这本书覆盖了除C语言以外的几乎所有主流编程语言。通过这本书,你可以从中学到编程语言背后的设计思想——编程语言为什么要被设计成这样,是什么促使设计者要在语言中加入这个特性(或拒绝那个特性)。从而提升对编程语言的理解。

8. 界面设计






  • GUI设计禁忌 2.0:这本书指出了GUI设计的原则和常见误区,然后通过具体范例指出了如何避免这些误区。如果你的工作涉及到用户界面,那么这本书会为你减少很多麻烦;
  • 界面设计模式(第2版):这本书将用户界面中的常见元素/行为组织成彼此关联的模式,以便读者理解并举一反三,从而将其运用到自己的应用中;
  • 移动应用UI设计模式:类似于界面设计模式,但面向移动平台。它给出了iOS,Android,以及Windows Phones上常用的90余种界面设计模式,从而使得你不必把这些平台的应用挨个玩一遍也可以掌握各个平台的设计精髓。如果你主攻Android平台,那么Android应用UI设计模式会是更好的选择;
  • 配色设计原理版式设计原理:如果你读过写给大家看的设计书之后想继续深入学习设计,这两本书是不错的起点。

9. 交互设计


书如其名,通用设计法则给出了重要的125个设计原则,并用简练的语言和范例展示了这些原则的实际应用。每个原则都有对应的参考文献,以便读者进一步学习。我之所以推荐这本书,是因为:1. 程序员需要对设计有全面的认识;2. 程序员并不需要知道这些设计原则是怎么来的,知道怎么用即可。这本书很好的满足了这两个要求。


交互设计精髓是交互设计领域的圣经级著作。交互设计专家(以及VB之父)Alan Cooper在这本书中详细介绍了交互设计的原则,流程,以及方法,然后通过各种范例(主要来自桌面系统)展示了如何应用这些原则。



  • The Design of Everyday Things:交互设计领域的另一本经典之作,它通过解读人类行动背后的心理活动,展示了设计问题的根源,并给出了一系列方法用以解决设计问题(需要注意,尽管这本书有中译版,但中译版对应的是02年的旧版,而非13年的新版);
  • The Inmates Are Running the AsylumAlan Cooper的另一本经典,这本书非常辛辣的指出让不具备人机交互知识的程序员直接编写面向用户的软件就像让精神病人管理疯人院(The Inmates Are Running the Asylum),然后给出了一套交互设计流程以挽救这个局面;
  • 简约至上:交互式设计四策略:专注于把产品变的更加简单易用。作者通过删除,组织,隐藏,和转移这四个策略,展示了如何创造出简约优质的用户体验。


1. 职业规划




  • 卡耐基全集:非常著名的为人处世书籍。很多人把这本书归类到成功学,但我并不这么认为——在我看来,这本书教的更多的是如何成为一个让大家喜欢的人。作为天天和机器打交道的程序员,这套书会帮助我们与人打交道;
  • 沃顿商学院最受欢迎的谈判课:这本书不是教你去谈判,而是教你通过谈判(Negotiation)去得到更多(Getting more,这也是这本书的原书书名)。小到买菜砍价,大到争取项目,这本书中的谈判原则会让你收益良多;
  • 程序员健康指南:作为长期与计算机打交道的职业,程序员往往会受到各式各样疾病的困扰,这本书正是为了解决这个问题而出现:它从改善工作环境,调整饮食结构,预防头痛眼痛,以及进行室内/室外锻炼等方面出发,给出了一套全面且可行的程序员健康改善计划,以帮助程序员打造健康的身体。

2. 思维方式




Mastery is not about perfection. It’s about a process, a journey. The master is the one who stays on the path day after day, year after year. The master is the one who is willing to try, and fail, and try again, for as long as he or she lives.



  • 怎样解题:数学思维的新方法:不要被标题中的“数学思维”吓到,它并不仅仅只是一本数学解题书,它所提出的四步解题法(理解题目->拟定方案->执行计划->总结反思)适用于任何领域;
  • 暗时间刘未鹏所写的关于学习思维方法的文章集,既包含了他对学习方法的思考,也包含了大量进一步阅读的资源;
  • 批判性思维:带你走出思维的误区:这本书系统的分析了人类思维的常见误区,并针对各个误区给出了解决方案,从而帮助程序员养成严谨正确的思考方式;
  • Conceptual Blockbusting: A Guide to Better Ideas:与批判性思维相反,这本书专注于创造性思维(Creative Thinking),它分析了阻碍创造性思维的常见思维障碍(Blockbuster)以及这些思维障碍背后的成因,并给出了各种方法以破除这些障碍。

3. 求职面试







  • 编程之美:微软技术面试心得:恐怕是国内技术面试第一书,这本书里面的多数题目都曾经是国内IT企业面试的必问题目。这本书的缺点是它太旧而且被用滥了(以至于一些企业开始避免使用这本书上的题目)——但你可以把它当成一本算法趣题来读;
  • 剑指Offer:名企面试官精讲典型编程题:相对于东拼西凑的XX面试宝典,剑指Offer是一本少见的国产精品技术面试书籍,尽管这本书的技术面试题目不多(60余道),但作者为大多数题目都给出了不同方式的解法,并分析了这些解法之间的优劣,此外作者还以面试官的视角分析了技术面试的各个环节,从而帮助读者把握技术面试;
  • 人人都有好工作:IT行业求职面试必读:可以把它看做金领简历的补充阅读——这本书的特点在于它给出了非常详细的简历/求职信/电子邮件编写技巧,而这正是不少国内程序员所缺乏的。

4. 英语写作

The Only Grammar Book You'll Ever Need

词汇量决定阅读能力,语法决定写作能力。计算机专业词汇并不多,但精确性非常重要,因此每个程序员都应具备良好的英语语法,但程序员并不需要过于专业的英语语法——掌握常用语法并把它用对就可以。The Only Grammar Book You’ll Ever Need正好可以满足这个需求,尽管它篇幅不大(不足200页),却覆盖了英语中的关键语法以及常见错误。把这本书读两遍,它会大幅度提高你的英语写作能力。




  • 牛津英语用法指南(第3版):全面且权威的英语用法指南,它覆盖语法,词汇,发音,以及修辞等方面,并兼顾口语和书面语,以帮助读者掌握合理的英语用法(Proper English Usage)。不要被这本书的篇幅(1000多页)吓到——原书并没有这么厚,因为这本书被翻译成中文但又得保留原有的英文内容,所以它的篇幅几乎翻了一倍。考虑到这本书使用的词汇都很基础,所以我认为具有英语基础的读者直接阅读原版(Practical English Usage)会更合适;
  • 写作法宝:非虚构写作指南(30周年纪念版):详尽的非虚构(Non-Fiction)写作指南,无论你要写地方,技术,商务,运动,艺术,还是自传,你都可以从这本书中找到珍贵的建议;
  • 中式英语之鉴:中国人使用英语最大的问题就是会把中式思维掺杂其中,从而形成啰里啰嗦不伦不类的中式英语(Chinglish)。中式英语之鉴系统的探讨了中式英语以及其成因,然后根据成因对中式英语进行归类,并对每个类别给出了大量的实际案例以及修改建议。如果你想摆脱中式英语,那么这本书是绝好的起点。









  1. 编码:隐匿在计算机软硬件背后的语言
  2. 深入理解计算机系统 / Windows核心编程 / 程序员的自我修养
  3. 代码大全 / 程序员修炼之道
  4. 编程珠玑 / 算法概论 / 算法设计 / 编程之美
  5. C程序设计语言
  6. C++程序设计语言 / C++程序设计原理与实践 / Accelerated C++
  7. 计算机程序的构造与解释
  8. 代码整洁之道 / 实现模式
  9. 设计模式 / 敏捷软件开发(原则模式与实践)
  10. 重构


  1. C++编程思想
  2. Effective C++
  3. 深度探索C++对象模型
  4. C++语言的设计与演化
  5. C专家编程
  6. C陷阱与缺陷
  7. C语言接口与实现
  8. Lua程序设计
  9. 链接器和加载器
  10. COM本质论
  11. Windows核心编程
  12. 深入解析Windows操作系统
  13. 程序员修炼之道
  14. 代码大全
  15. UNIX编程艺术
  16. 设计模式
  17. 代码优化:有效使用内存
  18. 深入理解计算机系统
  19. 深入理解LINUX内核
  20. TCP/IP详解


  1. 代码大全
  2. 人月神话
  3. 编码:隐匿在计算机软硬件背后的语言
  4. 计算机程序设计艺术
  5. 程序员修炼之道
  6. 设计模式
  7. 计算机程序的构造与解释
  8. 重构
  9. C程序设计语言
  10. 算法导论


  1. 点石成金:访客至上的Web和移动可用性设计秘笈
  2. 重来:更为简单有效的商业思维
  3. 黑客与画家
  4. 清醒思考的艺术
  5. TCP/IP详解
  6. UNIX环境高级编程
  7. UNIX网络编程


  1. 算法概论
  2. Data Structure and Algorithms
  3. C程序设计语言
  4. UNIX操作系统设计
  5. 编译原理
  6. 计算机体系结构:量化研究方法
  7. 当下的幸福
  8. 异类:不一样的成功启示录

Jeff Atwood(Stackoverflow联合创始人)

  1. 代码大全
  2. 人月神话
  3. 点石成金:访客至上的Web和移动可用性设计秘笈
  4. 快速软件开发
  5. 人件
  6. The Design of Everyday Things
  7. 交互设计精髓
  8. The Inmates Are Running the Asylum
  9. GUI设计禁忌 2.0
  10. 编程珠玑
  11. 程序员修炼之道
  12. 精通正则表达式

Joel Spolsky(Stackoverflow联合创始人)


  1. 人件
  2. 人月神话
  3. 快速软件开发


  1. 代码大全
  2. 程序员修炼之道


  1. 禅与摩托车维修艺术
  2. 哥德尔、艾舍尔、巴赫:集异璧之大成
  3. 建筑模式语言


  1. 点石成金:访客至上的Web和移动可用性设计秘笈
  2. 交互设计精髓
  3. The Design of Everyday Things


  1. 漫步华尔街


  1. 写给大家看的设计书


  1. 影响力
  2. Helplessness On Depression, Development and Death


  1. 编码:隐匿在计算机软硬件背后的语言
  2. C程序设计语言

DHH(Ruby on Rails创始人)

  1. Smalltalk Best Practice Patterns
  2. 重构
  3. 企业应用架构模式
  4. 领域驱动设计
  5. 你的灯亮着吗?发现问题的真正所在


  1. 怎样花两年时间去面试一个人
  2. What is the single most influential book every programmer should read?
  3. Recommended Reading for Developers
  4. Book Reviews — Joel Spolsky
  5. The five programming books that meant most to me





15 Must Read Books for Entrepreneurs in Data Science

Source: http://www.analyticsvidhya.com/blog/2016/04/15-read-books-entrepreneurs-data-science/



The roots of entrepreneurship are old. But, the fruits were never so lucrative as they have been recently. Until 2010, not many of us had heard of the term ‘start-up’. And now, not a day goes by when business newspapers don’t quote them. There is sudden gush in the level of courage which people possess.

Today, I see 1 out of 5 person talking about a new business idea. Some of them even succeed too in establishing their dream company. But, only the determined ones sustain. In data science, the story is bit different.

The success in data science is mainly driven by knowledge of the subject. Entrepreneurs are not required to work at ground level, but must have sound knowledge of how it is being done. What algorithms, tools, techniques are being used to create products & services.

In order to gain this knowledge, you have two ways:

  1. You work for 5-6 years in data science, get to know things around and then start your business.
  2. You start reading books along the way and become confident to start in first few years.

I would opt for second option.

15 must read books for entrepreneurs in data science

Why read books ?

Think of our brain as a library. And, it’s a HUGE library.

How would an empty library look like? If I close my eyes and imagine, I see dust, spider webs, brownian movement of dust particles and darkness. If this imagination horrifies you, then start reading books.

The books listed below gives immense knowledge and motivation in technology arena. Reading these books will give you the chance to live many different entrepreneurial lives. Take them one by one. Don’t get overwhelmed. I’ve displayed a mix of technical and motivational books for entrepreneurs in data science. Happy Reading!

List of Books

Data Science For Businessdata science for business vidhya

This book is written by Foster Provost & Tom Fawcett. It gives a great head start to anyone, who is serious about doing business with big data analytics. It makes you believe, data is now business. No business in the world, can now sustain without leveraging the power of data. This books introduces you to real side of data analysis principles and algorithms without technical stuff. It gives you enough intuition and confidence to lead a team of data scientists and recommend what’s required. More importantly, it teaches you the winning approach to become a master at business problem solving.

Get the book: Buy Now

Big Data at Workb2

This book is written by Thomas H. Davenport. It reveals the increasing importance of big data in organizations. It talks with interesting  numbers, researches and statistics. So until 2009, companies worked on data samples. But with advent of powerful devices and data storage capabilities, companies now work on whole data. They don’t want to miss even a single bit of information. This book unveils the real side of big data, it’s influence on our daily lives, on companies and our jobs. As an entrepreneur, it is extremely important for you understand big data and its related terminologies.

Get the book: Buy Now

Lean Analyticsb3

This book is written by Alistair Croll and Benjamin Yoskovitz. It’s one of the most appreciated books on data startups. It consist of practical & detailed researches, advice, guidance which can help you to build your startup faster. It gives enough intuition to build data driven products and market them. The language is simple to understand. There are enough real world examples to make you believe, a business needs data analytics like a human needs air. To an entrepreneur, this will introduce the practical side of product development and what it takes to succeed in a red ocean market.

Get the book: Buy Now


This book is written by Michael Lewis. It’s a brilliant tale which sprinkles some serious inspiration. A guy named billy bean does what most of the world failed to imagine, just by using data and statistics. He paved the path to victory when situations weren’t favorable. Running a business needs continuous motivation. This can be a good place to start with. However, this book involves technical aspects of baseball. Hence, if you don’t know baseball, chances are you might struggle in initial chapters. A movie also has been made on this book. Do watch it!

Get the book: Buy Now

Elon Muskb5

This book is written by Ashlee Vance. I’m sure none of us are fortunate to live the life of Elon Musk, but this book let’s us dive in his life and experience rise of fantastic future. Elon is the face behind Paypal, Tesla and SpaceX. He has dreamed of making space travel easy and cheap. Recently, he was applauded by Barack Obama for the successful landing of his spaceship in an ocean. People admire him. They want to know his secrets and this is where you can look for. As on entrepreneur, you will learn about must have ingredients which you need to a become successful in technology space.

Get the book: Buy Now

Keeping up with the Quantsb6

This book is written by Thomas H Davenport and Jinho Kim. As we all know, data science is driven by numbers & maths (quants). Inspired from moneyball, this book teaches you the methods of using quantitative analysis for decision making. An entrepreneur is a terminal of decision making. One must learn to make decisions using numbers & analysis, rather than intuition. The language of this book is easy to understand and suited for non-maths background people too. Also, this book will make you comfortable with basics statistics and quantitative calculations in the world of business.

Get the book: Buy Now

The Signal and the NoiseCover of the book 'The Signal and the Noise' by Nate Silver. Published by The Penguin Press

The author of this book is Nate Silver, the famous statistician who correctly predicted US Presidential elections in 2012. This books shows the real art and science of making predictions from data. This art involves developing the ability to filter out noise and make correct predictions. It includes interesting examples which conveys the ultimate reason behind success and failure of predictions. With more and more data, predictions have become prone to noise errors. Hence, it is increasingly important to understand the science behind making predictions using big data science. The chapters of this book are interesting and intuitive.

Get the book: Buy Now

When Genius Failedb8

This book is written by Roger Lowenstein. It is an epic story of rise and failure of a hedge fund. For an entrepreneur, this book has ample lessons on investing, market conditions and capital management. It’s a story of a small bank, which used quantitative techniques for bond pricing throughout the world and ensured every invested made gives a profitable results. However, they didn’t sustain for long. Their quick rise was succeeded by failure. And, the impact of their failure was so devastating that US Federal bank stepped in to rescue the bank, because the fund’a bankruptcy would have large negative influence on world’s economy.

Get the book: Buy Now

Lean Startupb9

This book is written by Eric Ries. In one line, it teaches how to not to fail at the start of your business. It reveals proven strategies which are followed by startups around the world. It has abundance of stories to make you walk on the right path. An entrepreneur should read it when he/she feel like draining out of motivation. It teaches to you to learn quickly, implement new methods and act quickly if something doesn’t work out. This book applies to all industries and is not specific to data science.

Get the book: Buy Now

Web Analytics 2.0

b10This book is written by Avinash Kaushik. It is one of the best book to learn about web analytics. Internet is the fastest mode of collecting data. And, every entrepreneur must learn the art of internet accounting. Most of the businesses today face the challenge of weak presence on social media and internet platforms. Using various proven strategies and actionable insights, this book helps you to solve various challenges which could hamper your way. It also provides a winning template which can be applied in most of the situations. It focuses on choosing the right metric and ways to keep them in control.

Get the book: Buy Now

Predictive Analyticsb11

This book is written by Eric Seigel. It is a good follow up book after web analytics 2.0. So, once you’ve understood the underlying concept of internet data, metrics and key strategies. This book teaches you the methods of using that knowledge to make predictions. It’s simple to understand and covers many interesting case studies displaying how companies predict our behavior and sell us products. It doesn’t cover technical aspects, but explains the general working on predictive analytics and its applications. You can also check out this funny rap video by Dr. Eric Seigel:

Get the book: Buy Now


This book is written by Steven D Levitt and Stephen J Dubner. It shows the importance of numbers, data, quantitative analysis using various interesting stories. It says, there is a logic is everything which happens around us. Reading this book will make you aware of the unexplored depth at which data affects our real lives. It draws interesting analogy between school teachers and sumo wrestlers. Also, the bizarre stories featuring cases of criminal acts, real-estate, drug dealers will certainly add up to your exciting moments.

Get the book: Buy Now

Founders at Workb13

This book is written by Jessica Livingston. Again, this isn’t data science specific but a source of motivation to get you moving forward. It’s a collection of interviews with the founders of various startups across the world. The focus has been kept on early days i.e. how did they act when they started. This book will give you enough proven ideas, strategies and lessons to anticipate and avoid pitfalls in your initial days of business. It consist of stories by Steve Wozniak (Apple), Max Levchin (Paypal), Caterina Fake (Flikr) and many more. In total, there are 32 interviews listed which means you have the chance to learn from 32 mentors in one single book. Must read for entrepreneurs.

Get the book: Buy Now

Bootstrapping a Businessb14

This book is written by Greg Gianforte and Marcus Gibson. It teaches about the things to do when you are running short of money and still don’t want to stop. This is a must read book for every entrepreneur. Considering the amount of investment required in data science startups, this book should have a special space in an entrepreneur’s heart. It reveals various eye opening truths and strategies which can help you build a great company. Greg and Marcus proves that money is not always the reason for startup failure, it’s all about founder’s perspective. This book has stories of success and failures, again a great chance for you to live many lives by reading this book.

Get the book: Buy Now

Analytics at Workb15

This book is written by Thomas H Davenport, Jeanne G Harris and Robert Morrison. This books reveals the increased use of analytical tools & concepts by managers to make informed business decisions. The decision making process has accelerated. For a greater impact, it also consists of examples from popular companies like hotels.com, best buy and many more. It talks about recruiting, coordination with people and the use of data and analytics at an enterprise level. Many of us are aware of data and analytics. But, only a few know how to use them together. This quick book has it all !

Get the book: Buy Now

End Notes

This marks the end of this list. While compiling this list, I realized most of these books are about sharing experience and learning from the mistake of others. Also, it is immensely important to posses quantitative ability to become good in data science. I would suggest you to make a reading list and stick to it throughout the year. You can take up any book to start. I’d suggest to start with a motivational book.

Have you read any other book ? What were your key takeaways? Did you like reading this article? Do share your knowledge & experiences in the comments below.

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