《统计思维：程序员数学之概率统计程序员数学之概率统计》pdf下载在线阅读全文，求百度网盘云资源

《统计思维》（Allen BDowney）电子书网盘下载免费在线阅读

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书名：统计思维

作者：Allen BDowney

译者：张建锋

豆瓣评分：67

出版社：人民邮电出版社

出版年份：2013-5

页数：160

内容简介：

代码跑出来的概率统计问题；

程序员的概率统计开心辞典；

开放数据集，全代码攻略。

现实工作中，人们常被要求用数据说话。可是，数据自己是不能说话的，只有对它进行可靠分析和深入挖掘才能找到有价值的信息。概率统计是数据分析的通用语言，是大数据时代预测未来的根基。

站在时代浪尖上的程序员只有具备统计思维才能掌握数据分析的必杀技。本书正是一本概率统计方面的入门图书，但视角极为独特，折射出大数据浪潮的别样风景。作者将基本的概率统计知识融入Python编程，告诉你如何借助编写程序，用计算而非数学的方式实现统计分析。一个趣味实例贯穿全书，生动地讲解了数据分析的全过程：从采集数据和生成统计量，到识别模式和检验假设。一册在手，让你轻松掌握分布、概率论、可视化以及其他工具和概念。

程序员的数学思维修炼（趣味解读）-等，周颖mobi

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天赋可以对成为一名优秀的程序员有一定的帮助，但不是必要的条件。更重要的是，成为一名优秀的程序员需要大量的学习和练习，以及对解决问题的热情和耐心。

虽然一些人在编程方面可能会比其他人更有天赋，但这并不意味着其他人无法成为优秀的程序员。相反，通过不断地学习和练习，任何人都可以逐渐提高自己的编程技能，并成为一名优秀的程序员。

此外，作为程序员，除了技术方面的能力外，还需要具备良好的沟通能力、解决问题的能力、团队合作精神等软技能。这些能力同样需要学习和练习，并不是天赋所能决定的。

First: programmers don't think they need to know math I hear that so often; I hardly know anyone who disagrees Even programmers who were math majors tell me they don't really use math all that much! They say it's better to know about design patterns, object-oriented methodologies, software tools, interface design, stuff like that 首先:程序员不认为他们需要了解数学我常常听到这样的话;我不知道还有没有不同意的甚至于以前是主修数学的程序员也告诉我他们真的不是常常使用到数学!他们说更重要的是要去了解设计模式,面向对象原理,软件工具,界面设计,以及一些其他类似的东西 And you know what They're absolutely right You can be a good, solid, professional programmer without knowing much math 你了解吗他们完全正确你不需要了解很多数学你就能做个很棒,很专业的程序员 But hey, you don't really need to know how to program, either Let's face it: there are a lot of professional programmers out there who realize they're not very good at it, and they still find ways to contribute 但是呢,同时你也不是真的需要知道如何来编程我们要面对的是:有很多专业的程序员,他们认识到他们不是非常擅长数学,但他们还是寻找方法去提升 If you're suddenly feeling out of your depth, and everyone appears to be running circles around you, what are your options Well, you might discover you're good at project management, or people management, or UI design, or technical writing, or system administration, any number of other important things that "programmers" aren't necessarily any good at You'll start filling those niches (because there's always more work to do), and as soon as you find something you're good at, you'll probably migrate towards doing it full-time 如果你突然觉得自己好烂,周围的人都远远的超过你,你会怎么想呢好,你可能会发现自己善于项目管理,或人事管理,或界面设计,或技术写作,或系统管理,还有许多其他程序员不必去精通的你会开始堆积那些想法(因为工作永远干不完),当你发现一些你能掌握的东西时,你很可能会转移去全职的做这个工作 In fact, I don't think you need to know anything, as long as you can stay alive somehow 实际上,我认为有些东西你不需要了解,当前你还能够赖以生存的话 So they're right: you don't need to know math, and you can get by for your entire life just fine withoutit 所以他们是对的:你不需要了解数学,并且没有数学你也能过的很好 But a few things I've learned recently might surprise you: 但是最近我学到一些东西可能会让你也感到惊喜:They teach math all wrong in school Way, WAY wrong If you teach yourself math the right way, you'll learn faster, remember it longer, and it'll be much more valuable to you as a programmer 学校里教数学的方式都错了仅仅是教学的方法错了,不是教数学本身错如果你以正确的方式学习数学的话,你会学的更快,记住这点,对你,作为一个程序员来说很有价值Knowing even a little of the right kinds of math can enable you do write some pretty interesting programs that would otherwise be too hard In other words, math is something you can pick up a little at a time, whenever you have free time 哪怕了解一点点相关的数学知识,就能让你写出可爱有趣的程序,否则会有些小难度换句话讲,数学是可以慢慢学的,只要你有时间Nobody knows all of math, not even the best mathematicians The field is constantly expanding, as people invent new formalisms to solve their own problems And with any given math problem, just like in programming, there's more than one way to do it You can pick the one you like best 没人能了解所有的数学,就是最棒的数学家也不是当人们发明新的形式去解决自己的问题时,数学领域就不断的扩展一些给出的数学问题,也正如编程,不止一种方法可以去解决他你可以挑个你最喜欢的方式Math is ummm, please don't tell anyone I said this; I'll never get invited to another party as long as I live But math, well I'd better whisper this, so listen up: (it's actually kinda fun) 数学是嗯,请别告诉别人我说过这个哈;当然我也不指望谁能邀请我参加这样的派对,在我还活着的时候但是,数学其实就是我还是小声的说吧,听好了:(她其实就是一种乐趣啦!) The Math You Learned (And Forgot) 你学到的数学(和你忘了的数学) Here's the math I learned in school, as far as I can remember: 这儿是我能记得的在学校学到的数学: Grade School: Numbers, Counting, Arithmetic, Pre-Algebra ("story problems") 初中:数,数数,算术知识,初级代数("带问题的小故事") High School: Algebra, Geometry, Advanced Algebra, Trigonometry, Pre-Calculus (conics and limits) 高中:代数,几何,高等代数,三角学,微积分先修课 (二次曲线论和极限) College: Differential and Integral Calculus, Differential Equations, Linear Algebra, Probability and Statistics, Discrete Math 大学:微积分,微分公式,线性代数,概率和统计,离散数学 How'd they come up with that particular list for high school, anyway It's more or less the same courses in most US high schools I think it's very similar in other countries, too, except that their students have finished the list by the time they're nine years old (Americans really kick butt at monster-truck competitions, though, so it's not a total loss) 上面那个关于高中数学课程单子上所列的,怎么来着美国高中几乎都是这样的课程设置我认为其他国家也会很相似的,除了那些在9岁之前就掌握了这些课程的学生(美国小孩同时却在热衷于玩魔鬼卡车竞赛,虽然如此,整个来说也算不上什么大损失) Algebra Sure No question You need that And a basic understanding of Cartesian geometry, too Those are useful, and you can learn everything you need to know in a few months, give or take But the rest of them I think an introduction to the basics might be useful, but spending a whole semester or year on them seems ridiculous 代数是的没问题你需要代数和一些理解解析几何的知识那些很有用,并且在以后几个月里,你能学到一切你想要的,十拿九稳的剩下的呢我认为一个基本的介绍可能会有用,但是在这上面花整个学期或一年就显得很荒谬了 I'm guessing the list was designed to prepare students for science and engineering professions The math courses they teach in and high school don't help ready you for a career in programming, and the simple fact is that the number of programming jobs is rapidly outpacing the demand for all other engineering roles 我现在意识到那个书单列表原是设计来准备给那些以后要当科学家和工程师的学生的他们在高中里所教的数学课程并不是为你的编程生涯做准备的,简单的事实是,多数的编程工作所需要的数学知识相比其他作为工程师角色的人所需要的数学增长的更快 And even if you're planning on being a scientist or an engineer, I've found it's much easier to learn and appreciate geometry and trig after you understand what exactly math is — where it came from, where it's going, what it's for No need to dive right into memorizing geometric proofs and trigonometric identities But that's exactly what high schools have you do 即使你打算当一名科学家或者一名工程师,在你理解了什么是数学之后-- 数学它如何而来,如何而去,为何而生,我发现这更加容易去学习和欣赏几何学和三角学不必去专研记住几何上的证明和三角恒等式,虽然那确实是高中学校要求你必须去做的 So the list's no good anymore Schools are teaching us the wrong math, and they're teaching it the wrong way It's no wonder programmers think they don't need any math: most of the math we learned isn't helping us 所以这样的书单列表不再有什么用了学校教给我们的不是最合适的数学,并且方式也不对不奇怪程序员认为他们不再需要数学:我们学的大部分数学知识对我们的工作没什么大的帮助 The Math They Didn't Teach You 他们没有教给你的那部分数学 The math computer scientists use regularly, in real life, has very little overlap with the list above For onething, most of the math you learn in grade school and high school is continuous: that is, math on the real numbers For computer scientists, 95% or more of the interesting math is discrete: ie, math on the integers 在现实中,计算机科学家经常使用的数学,跟上面所列的数学仅有很小的重叠 举个例子,你在中学里学的大部分数学是连续性的:也就是说,那是作为实数的数学而对于计算机科学家来说,他们所感兴趣的95%也许更多的是离散性的:比如,关于整数的数学 I'm going to talk in a future blog about some key differences between computer science, software engineering, programming, hacking, and other oft-confused disciplines I got the basic framework for these (upcoming) insights in no small part from Richard Gabriel's Patterns Of Software, so if you absolutely can't wait, go read that It's a good book 我打算在以后的博客中再谈一些有关计算机科学,软件工程,编程,搞些有趣的东东,和其他常常令人犯晕的训练我已经从Richard Gabriel的软件的模式这本书中洞察到一个无关巨细的基本框架如果你明显的等不下去的话,去读吧是本不错的书 For now, though, don't let the term "computer scientist" worry you It sounds intimidating, but math isn't the exclusive purview of computer scientists; you can learn it all by yourself as a closet hacker, and be just as good (or better) at it than they are Your background as a programmer will help keep you focused on the practical side of things 到现在为止,不要让"计算机科学家"这个词困扰到你它听上去很可怕,其实数学不是计算机科学家所独有的领域,你也能作为一个黑客自学它,并且能做的和他们一样棒你作为一个程序员的背景将会帮助你保持只关注那些有实践性的部分 The math we use for modeling computational problems is, by and large, math on discrete integers Thisis a generalization If you're with me on today's blog, you'll be studying a little more math from now on than you were planning to before today, and you'll discover places where the generalization isn't true But by then, a short time from now, you'll be confident enough to ignore all this and teach yourself math the way you want to learn it 我们用来建立计算模型的,大体上是离散数学这是普遍的做法如果正好今天你在看这篇博客,从现在起你正了解到更多的数学,并且你会认识到那样的普遍做法是不对的从现在开始,你将有信心认为可以忽略这些,并以你想要的方式自学 For programmers, the most useful branch of discrete math is probability theory It's the first thing they should teach you after arithmetic, in grade school What's probability theory, you ask Why, it's counting How many ways are there to make a Full House in poker Or a Royal Flush Whenever you think ofa question that starts with "how many ways" or "what are the odds", it's a probability question And as it happens (what are the odds), it all just turns out to be "simple" counting It starts with flipping acoin and goes from there It's definitely the first thing they should teach you in grade school after you learn Basic Calculator Usage 对程序员来说,最有效的离散数学的分支是概率理论这是你在学校学完基本算术后的紧接着的课你会问,什么是概率理论呢你就数啊,看有多少次出现满堂彩或者有多次是同花顺 不管你思考什么问题如果是以"多少种途径"或"有多大几率的",那就是离散问题当他发生时,都转化成"简单"的计数抛个硬币看看 毫无疑问在他们教你基本的计算用法后他们会教你概率理论 I still have my discrete math textbook from college It's a bit heavyweight for a third-grader (maybe), but it does cover a lot of the math we use in "everyday" computer science and computer engineering 我还保存着大学里的离散数学课本可能他只占了三分之一的课程,但是它却涵盖了我们几乎每天计算机编程工作大部分所用到的数学 Oddly enough, my professor didn't tell me what it was for Or I didn't hear Or something So I didn't pay very close attention: just enough to pass the course and forget this hateful topic forever, because I didn't think it had anything to do with programming That happened in quite a few of my comp sci courses in college, maybe as many as 25% of them Poor me! I had to figure out what was important on my own, later, the hard way 也真是够奇怪的,我的教授从没告诉我数学是用来干吗的或者我也从来没有听说过种种原因吧所以我也从没有给以足够的注意:只是考试及格然后把他们都忘光,因为我不认为她还和编程有啥关系事情变化是我在大学学完一些计算机科学的课程之后,也许是25%的课程可怜啊!我必须弄明白什么对于自己来说是最重要的,然后再是向深度发展 I think it would be nice if every math course spent a full week just introducing you to the subject, in themost fun way possible, so you know why the heck you're learning it Heck, that's probably true for every course 我想,如果每门数学课都花上整整一周的时间,而只是介绍让你如何入门的话,那将非常不错,这是最有意思的一种假设,那么你知道了你正学习的对象是哪种怪物了怪物,大概对每一门课都合适 Aside from probability and discrete math, there are a few other branches of mathematics that are potentially quite useful to programmers, and they usually don't teach them in school, unless you're a math minor This list includes: 除了概率和离散数学外,还有不少其他的数学分支,可能对程序员相当的有用,学校通常不会教你的,除非你的辅修科目是数学这些数目列表包括:Statistics, some of which is covered in my discrete math book, but it's really a discipline of its own A pretty important one, too, but hopefully it needs no introduction 统计学,其中一些包括在我的离散数学课里,她的某些训练只限于她自身自然也是相当重要的,但想学的话不需要什么特别的入门 Algebra and Linear Algebra (ie, matrices) They should teach Linear Algebra immediately after algebra It's pretty easy, and it's amazingly useful in all sorts of domains, including machine learning 代数和线性代数(比如,矩阵)他们会在教完代数后立即教线性代数这也简单,这但相当多的领域非常有用,包括机器学习 Mathematical Logic I have a really cool totally unreadable book on the subject by Stephen Kleene, the inventor of the Kleene closure and, as far as I know, Kleenex Don't read that one I swear I've tried 20 times, and never made it past chapter 2 If anyone has a recommendation for a better introduction to this field, please post a comment It's obviously important stuff, though 数理逻辑我有相当完整的关于这门学科的书没有读,是Stephen Kleene写的,克林闭包的发明者,我所知道的还有就是Kleenex这个就不要读了我发誓我已经尝试了不下20次,却从没有读完第二章如果哪位牛掰有什么更好的入门建议的话可以给我推荐虽然,这明显是非常重要的一部分Information Theory and Kolmogorov Complexity Weird, eh I bet none of your high schools taught either of those They're both pretty new Information theory is (veeery roughly) about data compression, and Kolmogorov Complexity is (also roughly) about algorithmic complexity Ie, how small you can you make it, how long will it take, how elegant can the program or data structure be, things like that They're both fun, interesting and useful 信息理论和柯尔莫戈洛夫复杂性理论真不可思议,不是么我敢打赌没哪个高中会教你其中任何一门课程她们都是新兴的学科信息理论是(相当相当相当相当难懂)关于数据压缩,柯尔莫戈洛夫复杂性理论是(同样非常难懂)关于算法复杂度的也就是说,你要把它压缩的尽量小,你所要花费的时间也就变的越长,同样的,程序或数据结构要变得多优雅也有同样的代价他们都很有趣,也很有用There are others, of course, and some of the fields overlap But it just goes to show: the math that you'll find useful is pretty different from the math your school thought would be useful 当然,也有其他的一些因素,某些领域是重复的也拿来说说吧:你所发现有用的那部分数学,不同于那些你在学校里认为有用的数学 What about calculus Everyone teaches it, so it must be important, right 那微积分呢每个人都学它,所以它也一定是重要的,不对吗

《程序员的数学思维修炼（趣味解读）》（周颖）电子书网盘下载免费在线阅读

链接：> 提取码：av7c    

书名：程序员的数学思维修炼（趣味解读）

作者：周颖

豆瓣评分：55

出版社：清华大学出版社

出版年份：2014-4-1

页数：301

内容简介：

本书是一本专门为程序员而写的数学书，介绍了程序设计中常用的数学知识。本书门槛不高，不需要读者精通很多高深的数学知识，只需要读者具备基本的四则运算、乘方等数学基础知识和日常生活中的基本逻辑判断能力即可。本书拒绝枯燥乏味的讲解，而是代之以轻松活泼的风格。书中列举了大量读者都很熟悉，而且非常有趣的数学实例，并结合程序设计的思维和算法加以剖析，可以训练读者的数学思维能力和程序设计能力，进而拓宽读者的视野，增强职场竞争力。

本书共11章，分别介绍了数据的表示、神奇的素数、递归、排列组合、用余数进行数据分组、概率、复利、数理逻辑、推理、几何图形构造、统筹规划等程序设计中常用的数学知识，从而引导读者深入理解编程中的数学方法和思路。本书包含的实例有结绳记事、孪生素数、梅森素数、哥德巴赫猜想、阶乘、汉诺塔、斐波那契数列、乘法原理、加法原理、字符编码、密码长度、日历中的数学、心灵感应魔术、约瑟夫环、智叟分牛、百枚钱币鼓士气、庄家的胜率、中奖概率、用概率方法求π值、复利的威力、对折纸张、舍罕王的赏赐、三段论、选言推理、假言推理、关系推理、花盆摆放、残缺棋盘、丢失的线条、田忌赛马、背包问题等。

本书适合广大程序设计人员及数学爱好者阅读，尤其适合有一定程序设计经验，但还需要进一步加深对程序设计理解的人员阅读。本书对IT求职人员、信息学竞赛和大学生程序设计竞赛等参赛学员也有很好的参考价值。

作者简介：

毕业于电子科技大学。高级程序员、某软件公司的技术总监。擅长C和C++语言，对数据结构和算法有深入的研究。长期从事行业软件设计和团队管理工作，已十年有余。有着丰富的IT架构设计经验和行业咨询经验。负责过多个大型软件项目的开发工作。

在本科阶段，我本人参与过数学建模，我们团队最终也获得了全国一等奖的荣誉。在数学建模比赛中，程序员起到的是至关重要的作用，因为大部分工作都是由程序员去完成的。

程序员具体应做好以下工作：

1、你要去建模(要会微分方程, 机器学习算法, 图论)；

2、写程序搞定你的模型(做A题的话你要会数值分析, 有些地方也叫计算方法 至于决策树, 图论, PCA降维, 聚类分析什么的, 那就是程序员的老本行了)；

3、debug你的程序得到看上去正确的结果；

4、在论文里面详细的描述你的算法和实现过程。

数学建模竞赛的最佳配置是每一个人都具备这4个能力。此外，文献检索和文献阅读能力也很重要。阅读文献是多么的重要，更不要说有些人完全靠吹牛来做数学建模，这是我个人的深刻体会。如果数学建模的三个人只有一个人具备这4个能力，那么恭喜你中奖了，工作几乎全部都是你来完成了。

关于编程你需要具备什么能力我认为有三点:

1、数据处理

对于需要数据支持的一些问题，我们必须收集数据，完成数据预处理，规范化数据格式，便于建模和求解。

2、代码编写

这部分是广泛的，但总之，你应该提前使用你的理论模型。一些问题可能会产生一些现成的代码，这些代码可以修改，但是问题并不多，而且大多数问题都需要重写。语言和工具是不受限制的，只要它能被实现。常用的MATLAB、Python、SAS、Lingo等，你可以看到我之前的回答:哪个软件更适合数学建模MATLAB是有限的-一个老司机回答的数学模型-

3、可视化

这是非常重要的。一个好的数学建模论文必须要有良好的视觉化，这就是要有高质量的。这可以在学术论文中引用。

总结

个人认为，程序员在数学建模中起到最重要的作用，如果一个团队里面只有一个程序员，那么这个人的工作量无疑是最大的。

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