Non trivial meaning4/1/2023 ![]() ![]() My student was interested in the problem of using machine learning to find geodesics in Cayley graphs. Given a graph $X$ we define a geodesic to be a path of minimal length among all paths joining two vertices $u,v \in V(X)$. So in a nutshell you should find, the more you code, the better quality of code you will produce.The following post is motivated by a discussion with one of my students and is also interesting as it gives a nice example of how notions of geometry can be used to study discrete structures. I also suspect most good programmers with years of programming experience find it easy to spot bad code. However, I suspect there is a correlation on how well someone understands their programming language and the quality of their code. One caveat would be you need to ensure the quality of the code in your portfolio is of a high standard.Īnd please don't ask how to tell if code is of a high standard as this always comes down to opinion. ![]() Then, once you have master those programming skills and you are looking to land a job, that is the time to concentrate on the portfolio.īut even then I really don't think you need to get overly concerned, because I suspect a modest portfolio would do just fine. Instead concentrate on learning how to actually write code using the language of your choice and for that endeavour trivial projects are just fine. When you are starting out you really don't need to spend time worrying about your portfolio. I was reading the FAQ for this subreddit and saw the recommendation to build up a portfolio of “non-trivial projects”. Hope that makes some sense, and best of luck with your PhD! Stuff like a moderately complex website, a desktop application for managing something you do, an in-depth and insightful analysis of some data that you collected and cleaned that reveals something meaningful, stuff like that. ![]() It doesn't have to be as ground-breaking as a publishable research paper, but it should be enough that people look at it and think it's kind of cool and not easy to do. Non-trivial stuff is typically work that takes several months to do (maybe less if you do it full time), solves a meaningful problem you have, and is at least somewhat original. And then there's just plain easy stuff, like maybe you made a 3 page static website or you made some plots using the Titanic dataset. Same with things like course projects and things you did by following a tutorial, even if you put a bit of your own spin on it. Great to do it, and maybe if you do a few hundred it would impress people who know about it, but generally not worth putting on the resume. Short projects that solve a problem for the sake of practice, like Project Euler, are trivial even if they're hard. Small demos can be non-trivial as well, but generally have to offer something particularly original/unique. IMO a non-trivial project, in general terms, is one that demonstrates commitment, structure, polish, and (usually) a variety of skills/technologies. Using a graphics API to get a shape moving on the screen is trivial finishing a game, even a small/simple one, is non-trivial. For example, using a pre-existing statistics library to solve one problem is trivial writing that library and documenting it is non-trivial. What that kind of time generally equates to is projects that are full-fledged "applications" or suites of functionality as opposed to solving one particular problem or exercise. A project that takes at least a week or so of solid work (and that's time spent doing substantive work building out the actual project, not time spent studying as a precursor to the project) is inherently non-trivial. ![]() I think the major factor that makes a project "non-trivial", regardless of skill level or field, is time. Again, I would love to hear everyone’s thoughts on this matter. I am I perhaps ignorant of the subtleties of when translating these ideas into working code? I just feel like some of the things I find “trivial” might not in fact be trivial and vice versa: some of the things I find nontrivial may in fact be entirely trivial. Also, I feel very comfortable with the statistical theory behind data analysis and concepts like gradient descent. I have been doing some of the project Euler exercises and those seem “trivial” enough in terms of how to solve. I have a MS in pure math and will be starting a PhD in math this Fall. I was wondering if people could share some insights and/or opinions about this matter.Ī little bit about myself. Of course being new to programming, I am ignorant of what the industry and community would consider non-trivial. Hello! I am a beginning to learn Python with an eye towards data science and machine learning. ![]()
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