Best products from r/argentina
We found 31 comments on r/argentina discussing the most recommended products. We ran sentiment analysis on each of these comments to determine how redditors feel about different products. We found 465 products and ranked them based on the amount of positive reactions they received. Here are the top 20.
1. Language Implementation Patterns: Create Your Own Domain-Specific and General Programming Languages (Pragmatic Programmers)
Pragmatic Bookshelf
2. Compilers: Principles, Techniques, and Tools (2nd Edition)
- O Reilly Media
Features:
3. How to Solve It: A New Aspect of Mathematical Method (Princeton Science Library)
- Princeton University Press
Features:
5. Labyrinths (New Directions Paperbook)
- New Directions Publishing Corporation
Features:
6. The Algorithm Design Manual
- More and Improved Homework Problems
- Self-Motivating Exam Design
- Take-Home Lessons
- Links to Programming Challenge Problems
- More Code, Less Pseudo-code
Features:
8. Computer Organization and Design MIPS Edition: The Hardware/Software Interface (The Morgan Kaufmann Series in Computer Architecture and Design)
- Morgan Kaufmann Publishers
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9. Concepts, Techniques, and Models of Computer Programming (The MIT Press)
- Used Book in Good Condition
Features:
10. Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World, 3rd Edition
11. Computer Graphics: Principles and Practice (3rd Edition)
- Tarp Is Lightweight Yet Durable, Manufactured From High-Density Polyethylene And Woven Into Fabric And Then Laminated Brown On Both Sides Then Finished By Hemming The Edges With Poly Twine Inserted In Hem
- All seams and hems are heat sealed
- UV Treated.
Features:
13. Stories from Latin America / Historias de Latinoamérica, Premium Third Edition
14. Fluent Forever: How to Learn Any Language Fast and Never Forget It
- Harmony
Features:
17. Transaction Processing: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)
18. The Design and Implementation of the FreeBSD Operating System (2nd Edition)
- Addison-Wesley Professional
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> # Teach Yourself Computer Science
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> If you’re a self-taught engineer or bootcamp grad, you owe it to yourself to learn computer science. Thankfully, you can give yourself a world-class CS education without investing years and a small fortune in a degree program 💸.
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> There are plenty of resources out there, but some are better than others. You don’t need yet another “200+ Free Online Courses” listicle. You need answers to these questions:
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> - Which subjects should you learn, and why?
> - What is the best book or video lecture series for each subject?
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> This guide is our attempt to definitively answer these questions.
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> ## TL;DR:
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> Study all nine subjects below, in roughly the presented order, using either the suggested textbook or video lecture series, but ideally both. Aim for 100-200 hours of study of each topic, then revist favorites throughout your career 🚀.
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> Subject Why study? Best book Best videos Programming Don’t be the person who “never quite understood” something like recursion. Structure and Interpretation of Computer Programs Brian Harvey’s Berkeley CS 61A Computer Architecture If you don’t have a solid mental model of how a computer actually works, all of your higher-level abstractions will be brittle. Computer Organization and Design Berkeley CS 61C Algorithms and Data Structures If you don’t know how to use ubiquitous data structures like stacks, queues, trees, and graphs, you won’t be able to solve hard problems. The Algorithm Design Manual Steven Skiena’s lectures Math for CS CS is basically a runaway branch of applied math, so learning math will give you a competitive advantage. Mathematics for Computer Science Tom Leighton’s MIT 6.042J Operating Systems Most of the code you write is run by an operating system, so you should know how those interact. Operating Systems: Three Easy Pieces Berkeley CS 162 Computer Networking The Internet turned out to be a big deal: understand how it works to unlock its full potential. Computer Networking: A Top-Down Approach Stanford CS 144 Databases Data is at the heart of most significant programs, but few understand how database systems actually work. Readings in Database Systems Joe Hellerstein’s Berkeley CS 186 Languages and Compilers If you understand how languages and compilers actually work, you’ll write better code and learn new languages more easily. Compilers: Principles, Techniques and Tools Alex Aiken’s course on Lagunita Distributed Systems These days, most systems are distributed systems. Distributed Systems, 3rd Edition by Maarten van Steen 🤷
>
> ## Why learn computer science?
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> There are 2 types of software engineer: those who understand computer science well enough to do challenging, innovative work, and those who just get by because they’re familiar with a few high level tools.
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> Both call themselves software engineers, and both tend to earn similar salaries in their early careers. But Type 1 engineers grow in to more fullfilling and well-remunerated work over time, whether that’s valuable commercial work or breakthrough open-source projects, technical leadership or high-quality individual contributions.
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> Type 1 engineers find ways to learn computer science in depth, whether through conventional means or by relentlessly learning throughout their careers. Type 2 engineers typically stay at the surface, learning specific tools and technologies rather than their underlying foundations, only picking up new skills when the winds of technical fashion change.
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> Currently, the number of people entering the industry is rapidly increasing, while the number of CS grads is essentially static. This oversupply of Type 2 engineers is starting to reduce their employment opportunities and keep them out of the industry’s more fulfilling work. Whether you’re striving to become a Type 1 engineer or simply looking for more job security, learning computer science is the only reliable path.
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> ## Subject guides
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> ### Programming
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> Most undergraduate CS programs start with an “introduction” to computer programming. The best versions of these courses cater not just to novices, but also to those who missed beneficial concepts and programming models while first learning to code.
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> Our standard recommendation for this content is the classic Structure and Interpretation of Computer Programs, which is available online for free both as a book, and as a set of MIT video lectures. While those lectures are great, our video suggestion is actually Brian Harvey’s SICP lectures (for the 61A course at Berkeley) instead. These are more refined and better targeted at new students than are the MIT lectures.
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> We recommend working through at least the first three chapters of SICP and doing the exercises. For additional practice, work through a set of small programming problems like those on exercism.
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> For those who find SICP too challenging, we recommend How to Design Programs. For those who find it too easy, we recommend Concepts, Techniques, and Models of Computer Programming.
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> [Structure and Interpretation of Computer Programs](https://teachyourselfcs.com//sicp.jpg)
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> ### Computer Architecture
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> Computer Architecture—sometimes called “computer systems” or “computer organization”—is an important first look at computing below the surface of software. In our experience, it’s the most neglected area among self-taught software engineers.
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> The Elements of Computing Systems, also known as “Nand2Tetris” is an ambitious book attempting to give you a cohesive understanding of how everything in a computer works. Each chapter involves building a small piece of the overall system, from writing elementary logic gates in HDL, through a CPU and assembler, all the way to an application the size of a Tetris game.
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> We recommend reading through the first six chapters of the book and completing the associated projects. This will develop your understanding of the relationship between the architecture of the machine and the software that runs on it.
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> The first half of the book (and all of its projects), are available for free from the Nand2Tetris website. It’s also available as a Coursera course with accompanying videos.
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> In seeking simplicity and cohesiveness, Nand2Tetris trades off depth. In particular, two very important concepts in modern computer architectures are pipelining and memory hierarchy, but both are mostly absent from the text.
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> Once you feel comfortable with the content of Nand2Tetris, our next suggestion is Patterson and Hennesy’s Computer Organization and Design, an excellent and now classic text. Not every section in the book is essential; we suggest following Berkeley’s CS61C course “Great Ideas in Computer Architecture” for specific readings. The lecture notes and labs are available online, and past lectures are on the Internet Archive.
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> ### Algorithms and Data Structures
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> We agree with decades of common wisdom that familiarity with common algorithms and data structures is one of the most empowering aspects of a computer science education. This is also a great place to train one’s general problem-solving abilities, which will pay off in every other area of study.
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> There are hundreds of books available, but our favorite is The Algorithm Design Manual by Steven Skiena. He clearly loves this stuff and can’t wait to help you understand it. This is a refreshing change, in our opinion, from the more commonly recommended Cormen, Leiserson, Rivest & Stein, or Sedgewick books. These last two texts tend to be too proof-heavy for those learning the material primarily to help them solve problems.
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> (continues in next comment)
OP, I would recommend the following assuming he will have access to a computer and the Internet and is somewhat comfortable using those things:
Here, is a link to a couple of them:
https://www.amazon.com/dp/1260011275/ref=sxbs_sxwds-stvp_1?pf_rd_m=ATVPDKIKX0DER&pf_rd_p=3341940462&pd_rd_wg=QhY2X&pf_rd_r=SNZ6KJ9YGJ9B3SS71HE8&pf_rd_s=desktop-sx-bottom-slot&pf_rd_t=301&pd_rd_i=1260011275&pd_rd_w=UvgyL&pf_rd_i=null&pd_rd_r=db451c8e-32db-4684-9246-6602f8168da5&ie=UTF8&qid=1517635806&sr=1
https://www.amazon.com/Stories-Mexico-Historias-M%C3%A9xico-Premium/dp/1260011046/ref=pd_sim_14_1?_encoding=UTF8&pd_rd_i=1260011046&pd_rd_r=QJRX7JC2P82FPT7PRKE3&pd_rd_w=we8to&pd_rd_wg=V7DKJ&psc=1&refRID=QJRX7JC2P82FPT7PRKE3&dpID=51aR236tnML&preST=_SY291_BO1,204,203,200_QL40_&dpSrc=detail
Whatever you do, you just want to make sure he is spending some time consistently on the big four: reading, talking, listening and writing. Obviously, a lot of time will also be spent on building his vocabulary as well.
Resumen de la noticia
>> “If our heart were large enough to love life in all its detail, we would see that every instant is at once a giver and a plunderer,” the French philosopher Gaston Bachelard wrote in contemplating our paradoxical experience of time in the early 1930s.
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>“It is the insertion of man with his limited life span that transforms the continuously flowing stream of sheer change … into time as we know it,” Hannah Arendt wrote half a century later in her brilliant inquiry into time, space, and our thinking ego.
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>It was later included in Labyrinths (public library) — the 1962 collection of Borges’s stories, essays, parables, and other writings, which gave us his terrific and timeless parable of the divided self.
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>> Borges begins by noting the deliberate paradox of his title, a contrast to his central thesis that the continuity of time is an illusion, that time exists without succession and each moment contains all eternity, which negates the very notion of “new.” The “slight mockery” of the title, he notes, is his way of illustrating that “our language is so saturated and animated by time.” With his characteristic self-effacing warmth, Borges cautions that his essay might be “the anachronistic reductio ad absurdum of a preterite system or, what is worse, the feeble artifice of an Argentine lost in the maze of metaphysics” — and then he proceeds to deliver a masterwork of rhetoric and reason, carried on the wings of uncommon poetic beauty.
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>> Writing in the mid-1940s — a quarter century after Einstein defeated Bergson in their landmark debate, in which science (“the clarity of metaphysics,” per Borges) finally won the contested territory of time from the dictatorship of metaphysics, and just a few years after Bergson himself made his exit into eternity — Borges reflects on his lifelong tussle with time, which he considers the basis for all of his books:
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>> Time, Borges notes, is the foundation of our experience of personal identity — something philosophers took up most notably in the 17th century, poets picked up in the 19th, scientists set down in the 20th, and psychologists picked back up in the 21st.
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>> Returning to Hume’s notion of the illusory self — an idea advanced by Eastern philosophy millennia earlier — Borges considers how this dismantles the very notion of time as we know it:
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Source Code | Tell me how to improve | Created by: u/Alawichu u/BaraBatman u/Craccini u/louislagrange
Here is the Amazon link to Che boludo and here's the link to Speaking argento
About books IN español argentino, I'm reading Papeles en el viento from Sacheri (the same guy who wrote the book in which El secreto de sus ojos is based. By the way, you should see that movie). Chapters are short and easy to read, and it's pure español argentino, with all of our attitudes and cursing :P
You need to learn some Spanish, then you can read this book to help you with our slang Che Boludo: A Gringo's Guide To Understanding The Argentines ($57 for a used book???).
Here is the scanned PDF.
This will come in handy.
Edit: saved you a few bucks.
Creo que mucha gente se confunde ser autodidacta con hacer algun cursito de como hacer una web y darle con eso.
Para llegar a cierto nivel, tenes que aprender computer science, teoria y trabajar en cosas que te permitan aplicar esa teoria.
Tenes que saber ver un algoritmo y poder calcular la complejidad, tenes que entender que son las patrones de diseño y cuando conviene aplicar tal o cual.
Tenes que entender como funciona OOP, pero tambien tenes que aprender algun lenguaje funcional, te va a hacer un programador más rico.
Tenes que entender de Unit Testing, automated testing, Integration testing.
Los dos libros que más me ayudaron cuando empecé en computer science son :
https://www.amazon.es/Algorithm-Design-Manual-Steven-Skiena/dp/1848000693
y
https://www.amazon.com/Design-Patterns-Elements-Reusable-Object-Oriented/dp/0201633612
Y ir codeando mientras vas leyendo y aplicando las cosas es fundamental.
Me parece que la diferencia entre ser autodidacta es que no tenés esa vara minima que te da la facultad, asi que depende de vos que tan crack queres ser y si estas dispuesto a poner el laburo y a aprender cosas constantemente.
La información esta en internet o Amazon, no hay ningún secreto.