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1 point

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8th Nov 2021

Yeah - you'd generally learn this stuff in a class on data structures and algorithms.

For self-study (I've never take a class myself), I found this textbook really helpful - there's a whole chapter on graph algorithms.

1 point

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3rd Oct 2020

I wish I had more to offer you. That sounds like a hard situation.

Are you averse to learning more web-related technologies? If I worked for a company that didn't respect my time like that, I would do the bare minimum to not get fired and put all my extra energy into learning new, more marketable skills.

FWIW - https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1848000693/ref=sr_1_3?crid=DMY3RYJUI0PN&dchild=1 is my go-to book for interview prep. It is framed in a way that helps you practice pattern matching of common computer science problems to options for data structures and algorithms that solve those problems. I have always done extremely well with whiteboarding/fast algorithm questions when I am grounded in the concepts of that book.

1 point

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21st Dec 2017

Getting to brute force is always a good first step. After that you have to be able to reason out where things take too much time, where you are doing too much work, where a loop could be replaced by something faster, where you might want to sacrifice memory for speed (or vice verse), and so on.

A lot of it ends up being very pattern-like, but to get there you have to get a firm understanding of the basics. Understand the situations where a (data structure) might be better than something else, or what type of problem you’re really looking at. Many problems can be reframed as a different problem, or are just variations of other problems.

To get there you will need to practice and develop that understanding. If you feel your DS&A are weak, then I’d recommend a book like <u>The Algorithm Design Manual</u>.

Also, 60% of the time, a hash table optimizes 100% of the time.

1 point

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20th Mar 2017

All in all a well formed opinion, however I disagree with recommending Introduction to Algorithms. Although it has "Introduction" in its title, I find it far too theoretical. In my opinion something like The Algorithm Design Manual works better.

1 point

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31st May 2015

I found this book to be massively helpful. For subjects that were a little bit harder to understand in the book, I turned to youtube. There are a lot of videos with good animated video representations of common algorithms. That really helped me comprehend and retain the information. Good luck!

40 points

·
23rd Sep 2016

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.

11 points

·
1st Apr 2019

leet code is a great place for practice problems

For algorithms this book is great https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1848000693/ref=sr_1_9?keywords=algorithms+book&qid=1554149281&s=gateway&sr=8-9

Also, if you are looking for a software engineering role you will also need to brush up on high level design like this video: https://www.youtube.com/watch?v=KmAyPUv9gOY

1 point

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12th Oct 2020

>Most of what I want from this education is a deeper understanding of algorithms and how to write more efficient code.

Hmmm, interesting. I would ask **why do you want to understand algorithms and write efficient code?** I'm going to guess you're still pretty young? Do you prefer theory or practical? If you *really* want to become a master of algorithms and love the math and science behind computers I would go and get a CS degree because that's exactly what that is. But CS has little to do with the practical problem-solving in tech.

A bootcamp will give you practical skills on how to solve problems with code, and that's exactly why I went. I wanted to build things, solve real-world problems, and get a job in tech where I would do both. Algorithms and the like are *super* important, but they're a tool, not a focus like in CS.

There's also nothing stopping you from picking up books like The Algorithm Design Manual, Clean Code: A Handbook of Agile Software Craftsmanship, or Clean Code: A Handbook of Agile Software Craftsmanship. You don't need a degree to get through these, just patience and persistence.

I went to https://www.fullstackacademy.com/ and it cost somewhere around $15,000 for a 3 month program. I was lucky enough to have some money saved up so didn't have to finance and the job I got double my previous salary so it's easily the best investment I've ever made.

1 point

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5th Sep 2020

No, just no. That is a grad-level textbook and challenging even at that level (and useless for application-focused readers). A far better choice for self-study might be the Algorithm Design Manual (lots of case studies), or Introduction to Algorithms: A Creative Approach (overpriced but I can get you a pdf), or Algorithms (very intuitive explanations). There is no reason to read CLRS unless you're preparing for grad school or enjoy proving theorems.

1 point

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29th May 2017

I personally like Skiena's book The Algorithm Design Manual https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1848000693

If you already studied algorithms but need a quick refresher, Algorithms in a Nutshell is good. https://www.amazon.com/Algorithms-Nutshell-OReilly-George-Heineman/dp/059651624X/ref=sr_1_3?s=books&ie=UTF8&qid=1496051402&sr=1-3&keywords=algorithms+in+a+nutshell

1 point

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14th Apr 2017

> Next semester I am taking Data Structures. I looked at data structure related questions and do not know the material to pass the interview questions. I simply haven't had the course yet.

You don't have to complete a data structures course in school to learn enough to get a job.

If I were you, I'd spend a couple weeks self-studying data structures & algorithms and then just apply. I'd recommend the Algorithm Design Manual. Go through the primary chapters, then tackle Leetcode easy problems (or CTCI). When you get stuck on a problem, go over the relevant section in the book(s). There's also a lot of info if you just google—wiki is often surprisingly good, visualgo is nice, etc.

1 point

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18th Mar 2017

> # Sin Humo Podcast
>
>

>

> ### Notas
>
> The Algorithm Design Manual: https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1848000693 Curso de Coursera de Algoritmos: www.coursera.org/specializations/algorithms Curso de Peter Norvig de Udacity: https://www.udacity.com/course/design-of-computer-programs--cs212 Programa 111Mil: www.argentina.gob.ar/111mil Autor de Homebrew (OSX) queda afuera de entervista de Google: news.ycombinator.com/item?id=9695102 Exercism.io, sitio para aprender lenguajes nuevos: www.exercism.io/ Ejercicio de "promises" (deferred) de entrevista: https://gist.github.com/fernandezpablo85/d020ea0efada7f5d4ab746f803ce723c

**empleadoEstatalBot**, aca es donde pongo huevadas pero hace rato que no se me ocurre ninguna.

[Autor](/u/subtepass) | Código fuente

1 point

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7th Dec 2016

Introduction to the Design and Analysis of Algorithms, by Levitin, was used at my university and none of us cared for that book and I don't recommend it.

I'm not familiar with #1, but I do recommend:

1 point

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29th Sep 2016

Back when I started the first book on algorithms was "Algorithms and Data Structures" by Niklaus Wirth. Now it's freely distributed by the author https://www.inf.ethz.ch/personal/wirth/

I heard good reviews about The Algorithm Design Manual by Steven Skiena, and Algorithms by Robert Sedgewick and Kevin Wayne; but I haven't read them myself.

1 point

·
23rd Sep 2016

I LOVE shopping online for books, so here are my recommendations:

- Start with Grokking Algorithms. It's the most approachable book on the subject that I know off (disclaimer, I've only read a couple chapters).
- After that, I'd try The Algorithm Design Manual. It's always highly recommended when people ask for algorithm books.
- The de-facto book on the subject is Introduction to Algorithms. It's commonly referred to as "CLRS", after the author's last names.

There are (in my opinion) no good Swift specific algorithm books out. The reviews for the available books are pretty bad.

PS: Grokking Algorithms is available through https://www.safaribooksonline.com/. They have a free 10-day trial.

1 point

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8th Feb 2016

I see The Algorithm Design Manual by Skiena recommended a lot.

1 point

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27th Jan 2016

You don't need very much mathematics at all to learn the implementations of various algorithms. Sure, many algorithms books have mathematics in them to analyze the performance of the algorithms, but if you are mostly interested in the details of the implementations of algorithms, rather than analysis of performance then there is nothing to hold you back.

The Algorithms Design Manual, by Steven Skiena would be a great starting point. http://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1848000693

Then, if and when your interest in analysis of performance increases you can move on to a more mathematically demanding book, such as Introduction to Algorithms, by Cormen et al. http://www.amazon.com/Introduction-Algorithms-Edition-Thomas-Cormen/dp/0262033844

1 point

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30th Nov 2015

You can consider getting him a maker space membership if he likes making things. :D

They are essentially spaces where you can drop in and collab with others to make cool things. They have tons of equipment that you can use (depends on the place, there's woodworking, 3D printing, electronics, etc.). It's awesome for meeting people and learning new tech.

Here are a few that you can check out:

- Site3 coLaboratory
- Hacklab (I think Hacklab actually requires the prospective member to drop in beforehand and get invited, but you can double check.)

But yeah, or CLRS. Heck, while you're at it, here are some other ballin textbooks that will serve as timeless references. (Someone already covered Cracking the Coding Interview, so leaving that out.)

1 point

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31st Mar 2015

These two are my absolute favorites:

The Algorithm Design Manual and Introduction to Algorithms

They have a quite different take on algorithms. I recommend them both, actually. CLRS (the Introduction to Algorithms) is a staple book in most courses. The Algorithm design manual has a more practical view of things, which might be really great to learn alongside the more technical stuff that CLRS teaches.

I will not recommend the Art of Computer Programming to prepare for an algorithms course. I own the books as a collection, but they will be too hard and focused on things that your algorithm course will just jump over. The other books I mentioned here are in my opinion better suited for that. I've never heard of Art of Computer programming being used in an algorithm course, except for small exempts of it. Also, without reading Knuths Concrete Mathematics (great book) or being well versed in the mathematics he uses, it will be extremely hard.

I've heard good stuff about Sedgwick's book as well, which nerga recommended.

0 points

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25th Sep 2016

Read up on algorithms https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1848000693

0 points

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16th Jun 2015

Get Skiena's book and read the algorithm war-stories at the end of each chapter.

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