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Advanced Data Structures (2017)

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Re: Advanced Data Structures (2017)

#21

Post by ascar »

joebergeron wrote: post #16
jammygit wrote: post #15

As a busy self-learner, when is it time to learn data structures in depth? I feel like there are always 10 other technologies I need to know more urgently (eg, more bash, Linux, testing frameworks, deep learning, c++ libraries, linear algebra, common security mistakes/attacks, OpenGL, etc)

Given the bulk of the things you've listed here, which seem to serve very practical purposes, maybe never. I wouldn't call data structures a "technology" so much as I would label them as a theoretical underpinning to much of computer science. If your goal is to learn practical technologies (which is a good goal!) you don't really _need_ to learn data structures deeply -- they're just not a skill you need in day-to-da…

>"they're just not a skill you need in day-to-day software life (for most people)."

I mostly disagree. You won't need to implement them, but a working knowledge of the basics is the basis of any performance analysis and can make a huge difference in system performance in day to day programming. At some point all the small inefficiencies also add up.

I would go so far as to say that data structures and basic algorithms (e.g. Dijkstra) are more important to become a competent engineer than any of the practical tools he listed. It's like the difference between a mechanic and a mechanical engineer.

There is also a reason they are taught very early in a computer science degree.

Re: Advanced Data Structures (2017)

#22

Post by mothas »

I happened to interact with Erik Demaine via an open source project(KaTex). It was my first OSS contribution and he was very welcoming and friendly. Of course, I was also humbled to read about his work.

Re: Advanced Data Structures (2017)

#24

Post by jolmg »

jammygit wrote: post #15

As a busy self-learner, when is it time to learn data structures in depth? I feel like there are always 10 other technologies I need to know more urgently (eg, more bash, Linux, testing frameworks, deep learning, c++ libraries, linear algebra, common security mistakes/attacks, OpenGL, etc)

As someone in the same situation as you, I can advice that it's better to hold off on learning such things until you have a good moment to make use of them.

I studied a lot of Intel's 64 and IA-32 Architectures Software Developer Manuals, particularly the first and third volumes, and have forgotten a lot of details of what I read. I should have waited until I was ready to invest time in writing an OS or a first-stage bootloader or something. The broader things were useful, but I learned a lot of details that I haven't used and have forgotten. I'm sure it's still useful in the sense that I can quickly pick it back up if I ever needed to, but still. Same for all those things I read from the OSDev Wiki.

Re: Advanced Data Structures (2017)

#25

Post by mrbill29 »

joebergeron wrote: post #16
jammygit wrote: post #15

As a busy self-learner, when is it time to learn data structures in depth? I feel like there are always 10 other technologies I need to know more urgently (eg, more bash, Linux, testing frameworks, deep learning, c++ libraries, linear algebra, common security mistakes/attacks, OpenGL, etc)

Given the bulk of the things you've listed here, which seem to serve very practical purposes, maybe never. I wouldn't call data structures a "technology" so much as I would label them as a theoretical underpinning to much of computer science. If your goal is to learn practical technologies (which is a good goal!) you don't really _need_ to learn data structures deeply -- they're just not a skill you need in day-to-da…

The only time this information is really helpful is if you care about optimization. If most of the data you deal with is within 1000 items, or there's no time/hardware constraint, then this isn't super helpful. But if you're trying to take a function that costs you tons of CPU time down, there may be some value in knowing how it all works under the hood, and how to improve it.

Re: Advanced Data Structures (2017)

#26

Post by zphds »

jammygit wrote: post #15

As a busy self-learner, when is it time to learn data structures in depth? I feel like there are always 10 other technologies I need to know more urgently (eg, more bash, Linux, testing frameworks, deep learning, c++ libraries, linear algebra, common security mistakes/attacks, OpenGL, etc)

Same here. I had the same problem especially when dealing with problems that required me to go back and (un)learn stuff from scratch.

I found that the greatest barrier to deal with seemingly hard concepts was getting the right intuition on what "might" be happening under the hood. For me, this is absolutely crucial even if my intuition about a "thing" might not be completely correct.

As someone who didn't go to a classroom to be taught a lot of the basics, I dive in head-first to read papers, I mean a lot of papers, to help build this mental model EVEN though I don't understand everything in it, but it lets you pick up patterns for solving similar problems you might be having.

For things you don't understand, you can always fit in these gaps in your mental model as you dig deeper into the abstraction cake and repeat the whole "intuition" building loop.

I find that the same also applies to Math and other domains which build on a bunch of primitives that has to be really well known to be able to reason in higher abstractions.

I feel software is no different... dig deep enough, there will be a hashmap of some sort.

Re: Advanced Data Structures (2017)

#27

Post by Koshkin »

Swizec wrote: post #18
joebergeron wrote: post #16

Earlier quoted context omitted.

Given the bulk of the things you've listed here, which seem to serve very practical purposes, maybe never. I wouldn't call data structures a "technology" so much as I would label them as a theoretical underpinning to much of computer science. If your goal is to learn practical technologies (which is a good goal!) you don't really _need_ to learn data structures deeply -- they're just not a skill you need in day-to-da…

> the idea of implementing so much as a binary heap In my experience knowing how to implement such things isn't very useful in daily practical programming. Knowing that they exist, what problems they solve, the pros and cons that is incredibly useful day to day. Especially if you can recognize when you've accidentally strayed into implementing one of them under the guise of solving a business problem. You can then ap…

Not to disagree, but even if one visits restaurants for their "day to day" meals, one might begin wondering, Hmm.. How would I cook that?

Re: Advanced Data Structures (2017)

#29

Post by mettamage »

jammygit wrote: post #15

As a busy self-learner, when is it time to learn data structures in depth? I feel like there are always 10 other technologies I need to know more urgently (eg, more bash, Linux, testing frameworks, deep learning, c++ libraries, linear algebra, common security mistakes/attacks, OpenGL, etc)

If I were you I'd send an email to prof. Erik Demaine about this. If you write your email thoughtfully enough, then I think he's the kind of person to answer. I would in his position send at least a quick reply.

I have the same question, except I already have a partial answer (i.e. less interested in going after it, I sometimes do these things if I'm interested enough). I'm currently working my way up 6.006, but I wonder why I'd have to do advanced data structures. My guess is: I think I don't, because it's more of a research area than anything else.

I would need to take a quick look to see if there are some interesting data structures solving some interesting problems.

Personally, I'd be interested in time travel and memory hierarchy (caching) as topics. I think they might have some immediate practical utility in those areas.

Re: Advanced Data Structures (2017)

#30

Post by knicholes »

jammygit wrote: post #15

As a busy self-learner, when is it time to learn data structures in depth? I feel like there are always 10 other technologies I need to know more urgently (eg, more bash, Linux, testing frameworks, deep learning, c++ libraries, linear algebra, common security mistakes/attacks, OpenGL, etc)

It depends if you're learning for pleasure or for your career. ;) When I bust out my algorithms/data structures books, I find myself engrossed much like I imagine people get with a good novel. So many times I say to myself, "Whoah! That's so cool!" because of how elegantly/efficiently a problem can be solved that I had never even considered.

My favorite so far is Skiena's "The Algorithm Design Manual". I especially love the computational geometry section.

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