(Part 3) Top products from r/argentina

	

	

	

> # 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 🤷‍
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> ## 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)

> Son innumerable (porque la evidencia de lo contrario jamás fue producida). Pero por poner un ejemplo, el propio Fondo Monetario lo reconoce, si quieres leer más, acá hay más detalles también.

Por favor decime exactamente la pagina o parrafo, es medio embole sino.

> La idea de que esto constituye contra ejemplos es risible

¿Por qué?

> No creo que estés familiarizado con la política económica de Alemania en esa época, ni mucho menos con las políticas públicas de los países que aparecen más altos en esa lista.

La mayoría son economías de mercado.

> Singapur el estado es básicamente omnipresente, dueño del 70% de la tierra (en HK es del 100), y en ambos países el estado tiene múltiples monopolios y es dueño parcial de las empresas privadas vía los fondos soberanos que controlan.

Singapur tiene bastantes problemas sociales, pero no tiene nada que ver con lo que estamos hablando. Estamos hablando de las políticas económicas que llevan a los países a ser desarrollados.

> Si tuvieras alguna idea del tipo de reformas agrarias que se hicieron en Japón y Corea del Sur te da un infarto, y el grado de redistribución que implicaron. Ni hablar del día que te enteres del comunismo de la codeterminación alemana.

Te pedí fuentes, no una vaga mención de "reformas agrarias"

Y no sé a qué te referís con "comunismo", nunca existió un país comunista, porque el comunismo require que no haya estado ni moneda.

> Que la distribución de ingresos es necesaria ni siquiera es controversial entre los economistas

Yo nunca dije que no sea necesaria ahora, dije que los países adquirieron riquezas abriendo su mercado y sacando restricciones, y después intervinieron en la economía.

> La evidencia de que la desigualdad es mala para el crecimiento económico es amplia, he aquí un ejemplo por la OECD, es decir, las políticas que atacan la desigualdad de manera efectiva incrementan el crecimiento económico en el futuro.

There is mixed evidence in the literature regarding the relationship between income inequality and economic growth. Some studies have found a positive relationship, others a negative relationship while some found no correlation between the two variable

​

Del mismo estudio eh..

https://www.researchgate.net/publication/320410820_The_Impact_of_Income_Inequality_On_Economic_Growth_A_Case_Study_On_Nigeria

> Ambos son falsos. En el segundo ejemplo, la evidencia es que ni siquiera tienden a ser más eficientes.

Depende a qué te referís con "eficiencia". Las empresas son más eficientes en cuanto a hacer la misma cantidad por menor costo. En ese sentido quizas el Estado es más "eficaz" en tanto y cuanto es más probable que "ayude" a una mayor cantidad de personas.

Realmente es trivial que las empresas privadas son más eficientes, de lo contrario los países con economías centralizadas hubieran sido un éxito.

> Los datos empíricos en contra de la austeridad expansiva son completamente overwhelming, y es básicamente el laughing stock de la economía contemporánea

Repetir lo mismo muchas veces no lo hace verdad.

> Por lo menos desde la credibility revolution. Lo demás requiere demasiados detalles, la cantidad de cosas que los economistas están a favor que le harían explotar la cabeza a la gente de derecha son incontables, desde impuestos sobre el valor de la tierra, a impuestos pigouvianos, a antitrust enforcement, a mil millones de cosas.

La pluralidad de economistas son de centro-derecha, así que es bastante cuestionable esa oración.

Te dejo un lindo artículo que basicamente contradice todo lo que decís, hecho por economistas de los dos lados.

https://www.nytimes.com/2015/04/26/upshot/economists-actually-agree-on-this-point-the-wisdom-of-free-trade.html?mcubz=0



>If economists are so sure about the benefits of free trade, why are the public and their elected representatives often skeptical? One answer comes from a 2007 book by Bryan Caplan, a George Mason University professor, called “The Myth of the Rational Voter: Why Democracies Choose Bad Policies.”
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>Mr. Caplan argues that voters are worse than ignorant about the principles of good policy. Ignorance would be random and might average out in a large population. Instead of being merely ignorant, voters hold on to mistaken beliefs.
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>Politicians, whose main goal is to get elected, mold those mistaken beliefs into bad policy. Mr. Caplan writes: “What happens if fully rational politicians compete for the support of irrational voters — specifically, voters with irrational beliefs about the effects of various policies? It is a recipe for mendacity.”
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>In the case of international trade, three biases that he identifies are most salient.
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>The first is an anti-foreign bias. People tend to view their own country in competition with other nations and underestimate the benefits of dealing with foreigners. Yet economics teaches that international trade is not like war but can be win-win.
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>The second is an anti-market bias. People tend to underestimate the benefits of the market mechanism as a guide to allocating resources. Yet history has taught repeatedly that the alternative — a planned economy — works poorly.
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>The third is a make-work bias. People tend to underestimate the benefit from conserving on labor and thus worry that imports will destroy jobs in import-competing industries. Yet long-run economic progress comes from finding ways to reduce labor input and redeploying workers to new, growing industries.
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>The Princeton economist Alan Blinder once proposed Murphy’s Law of economic policy: “Economists have the least influence on policy where they know the most and are most agreed; they have the most influence on policy where they know the least and disagree most vehemently.”
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>The debate about international trade is a case in point. In the coming weeks, members of Congress will have an opportunity to prove Mr. Blinder wrong. Let’s hope they take it.

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http://www.igmchicago.org/surveys/free-trade

Freer trade improves productive efficiency and offers consumers better choices, and in the long run these gains are much larger than any effects on employment.

56% agree

29% Strongly agree

Mirando: termine true detective, viendo house of cards, sigo con vikings y esperando game of thrones. Viendo si me le animo a Treme.

Leyendo: Room, de Emma Donoghue y The Master & Margarita, de Mickhail Bulgakov

Jugando: deje de ser "gamer" hace 10 años, me embola

https://www.amazon.com/Influence-Psychology-Persuasion-Robert-Cialdini/dp/006124189X


https://www.amazon.com/Laws-Power-Robert-Greene-Collection-ebook/dp/B0041G68Z0/ref=sr_1_1?s=books&ie=UTF8&qid=1469486862&sr=1-1&keywords=48+laws+power

http://www.amazon.com/People-Believe-Weird-Things-Pseudoscience/dp/0805070893

o

http://www.amazon.com/Philosophy-Pseudoscience-Reconsidering-Demarcation-Problem/dp/022605196X

Más que CCNA, empezaría por acá:

https://www.amazon.com/gp/aw/d/0201633469/ref=mp_s_a_1_1?ie=UTF8&qid=1498615690&sr=8-1&pi=AC_SX236_SY340_FMwebp_QL65&keywords=stevens+tcp+ip+illustrated&dpPl=1&dpID=51jbAgYTQ8L&ref=plSrch

El temario de IGCSE es muy completo. Considerá http://www.amazon.co.uk/Complete-Economics-Cambridge-O-level-Edition/dp/0199129584 o similar si tu interes es aprender

>Y que es lo que tenes que estudias para ser agente de viajes que acompañan a la gente?

Escort Premium o azafata.

Podés probar aprender C, que está bueno si queres saber como funciona un idioma de programación a nivel mas cercano al hardware. Si ya sabes programar podes usar este libro para aprender.

Mas adelante en la carrera me parecen que ven Haskell, pero probablemente sea demasiado avanzado si estás empezando.

Sobre japon podes preguntar en r/japanart

Este es medio canon introductorio:
https://www.amazon.com/History-Japanese-Art-Penelope-Mason/dp/0130163953/ref=sr_1_2?ie=UTF8&qid=1513511838&sr=8-2&keywords=History+of+Japanese+Art%27

Y:
https://www.amazon.com/How-Look-At-Japanese-Art/dp/0810926407/ref=pd_sim_14_1?_encoding=UTF8&pd_rd_i=0810926407&pd_rd_r=WNVEDJX8K7SC7H83VC8T&pd_rd_w=1wj3S&pd_rd_wg=6dyDh&psc=1&refRID=WNVEDJX8K7SC7H83VC8T

O cambiar de temas e intentar entender en profunidad las implicaciones de lo visto. Si alguien le da 3 hs seguidas en la misma seccion a Grimaldi se le funde el bocho.

Eso solo de estudiar y entender los conceptos. Hacer ejercicios o resolver los problemas creo que podes meterle facil como dice u/chabon22 varias horas. Total no te sale uno y pasas a otro o cambias a otra guia y ya.

Si estás hablando de Algebra Lineal, los libros de Serge Lang son buenísimos. Conciso explicando, pero no deja la intuición detrás. Tiene muchos ejercicios también si querés practicar.

Los libros son:
https://www.amazon.com/Introduction-Linear-Algebra-Undergraduate-Mathematics/dp/0387962050
https://www.amazon.com/Linear-Algebra-Undergraduate-Texts-Mathematics/dp/0387964126/ref=pd_bxgy_14_img_2?_encoding=UTF8&pd_rd_i=0387964126&pd_rd_r=JFJYRBF3JXJN1T8SNXK7&pd_rd_w=Ym5Mi&pd_rd_wg=d1H0O&psc=1&refRID=JFJYRBF3JXJN1T8SNXK7

Por ahí los podés encontrar en genlib para descargar.

edit: si podés ir a una clase de consulta mejor aún para cerrar un tema en particular, de ahí generalmente te vas con todo clarisimo

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.

The ascent of Money, de Niall Ferguson. Sino podés ver la serie del mismo nombre en YouTube, pero no es lo mismo.

Cuenta la historia económica del mundo y como fueron apareciendo los distintos instrumentos financieros hasta la crisis del 2008.

Prime es pago (36 euros por año en españa) pero si nunca tuviste podes sacar un trial (no te olvides de cancelarlo) de un mes.
Prime lo que hace es que las cosas lleguen en uno o dos dias. Sin prime, te llegan por ahi en 3 a 5 dias. Con prime no pagas costo extra de envio, que suele ser unos 5 euros. Ahora, generalmente para cosas caras no pagas envio aun sin prime. La diferencia es el tiempo.

Ojo con lo que compres porque en la pagina de amazon vas a encontrar diferentes tipos de productos:

• Los vendidos por Amazon (prime sirve ahi)
  
• Los vendidos por un tercero pero despachados por Amazon (fulfilled by Amazon) (Prime Sirve)
  
• Los vendidos por un tercero pero que Amazon no despacha (Prime no se usa ahi)
  
  Celulares, yo me compraria un Xiaomi Note 8, Note 8T, o similares antes que el 9SE.
  
  https://www.amazon.es/Xiaomi-8T-Bateria-4000mAh-Espa%C3%B1ola/dp/B00VI3MK4M/
  https://www.amazon.es/Xiaomi-Redmi-Note-Procesador-Snapdragon/dp/B07Y1D52LV/
  
  Ahora, fijate que sean compatibles con las bandas Argentinas.

Jo-der. No se si sos un economista, un biologo, o un sabelotodo -- pero la gente como vos es peligrosa... Agarras el narrativo ideal y lo justificas atacando la cruda realidad (y sin fundamento). Espero que seas un interlocutor valido o que por lo menos, vos tambien, tengas autores a quienes haces referencia.

Aca van los mios:

• Capitalismo como propiedad intrinseca de la poblacion humana:
  
  "The Delphic Boat: What Genomes Tell us" by: Antoine Danchin (un groso..... en serio.)
  
  "The Free Market Existentialist" by: William Irwin (phD philosophy).
  
  "Antifragile" by: Nassim Taleb (este tipo es una eminencia, lee su CV
  
  
  Ademas, tal vez te interese este video informativo (porque no tenes ganas de leer tanto) acerca de la historia del capitalismo... son 11 mins. y bastante claro.
  
  
• El gen como unidad basica
  
  "The Selfish Gene" by Richard Dawkins. (si no leiste esto todavia, te lo recomiendo!!!! mucho!!!!! pero me parece raro que seas biologo y no entiendas a lo que me refiero con decir que el gen es la unidad basica)
  
  
• Matematica para entender la economia desde los grados de libertad que se presentan en el movimiento Browniano (Stoic Calculus)
  
  Ito Calculus es un buen lugar para comenzar.
  
  Este video course de MIT acerca de finanzas es basicamente TODO la matematica que necesitas para entender finanzas o macroeconomia moderna.
  
  Este video course de MIT es mas orientado a la economia y el rol de la politica en el desarrollo economico.
  
  Cualquier duda NO QUEDO a disposicion por consultas, pero espero que contribuyas algo de tu parte.... para enriquecer la discusion
  
  Y a los downvoters: You're all dirty slags.
  
  EDIT - agregue un video