812 karma · joined January 12, 2022
One of those things that are not rocket science, yet is presented as such.
Like most algorithm courses are fairly abstract form of programming (writing a line of code) where as a working programmer is a software engineer constrained by time and resources. This means that for example this algorithm course, it teaches you to generalize your solutions but that's not always realistic goal, or even desirable goal, in software engineering, and you might find out this if you implement one of the algorithms to do something for you in a small program.
Applying what you've learned in some software project of yours constraints you nicely such that you can't waste your time reading stuff from cover to cover.
Just that if you need to understand differential equations, and you don't know calculus, the answer in this context isn't reading Spivak from start to finish (here I am assuming a working programmer / self-learner that wants to apply the knowledge - constrained by time and application much more heavily than a student of mathematics for example).
I talk about applying the knowledge a lot because it is a wonderful constraint, it makes it so that you don't accidentally read things cover to cover, but do like a depth first search into the subject instead.
I have friends 2 decades into programming as a profession who've never implemented any of these.
- but "took" more courses than necessary for my self-learning (I think I read through all of Logic / Language courses, insanely fascinating topic).
- I would not recommend a self-learner to follow it rigorously. Like if you are a working programmer, look for material that will help you at your work. Idea is to apply the knowledge.
- Some courses have assignments shared so that's great if you have the time check them out too. Definitely great for their database courses.
This was exactly how I taught myself, but I used CMU as my guide, lol. It is not hard to find good quality material, many universities have them open, but this curriculum is hard to 'graph' when you don't know where to start and what is an actual logical way to organize it.
So yeah, do this if you are a self-learner.
I think it stated that `=` "makes computer remember stuff", this is vocabulary aimed at 5 year olds.
- People presenting it as something hard to learn.
simplest systems programming lang ive ever used
There are generic answers:
- Refactoring business logic costs. That's why it doesn't happen often.
- Interop between two different codebases (new Julia, old Python) costs (both at an org scale and at programming scale).
- It's a new lang. Hiring new programmers to a new meme language is very risky. You lose that programmer, your project is in trouble.
- You are underrating Python ecosystem strength.
- Python first mover advantage.
There are Julia specific reasons:
- No Julia programmers outside of MIT where as everyone has touched Python.
- Python is "simpler".
- Last I read Julia has some growing pains, like REPL boot times?
> All talks are on-line and open to the public via Zoom. You do not need to be a current CMU student to attend. Random people off of the internet are especially welcome. Videos will be posted on the CMU-DB Youtube Channel after each talk.
This seminar from CMU starts tomorrow with Thomas Neumann. There are other interesting speakers too, like everyone's favorite SQLite article author
Are there algorithm courses that take into account how hardware affects algorithms? For example with databases, you have implement theoretically inefficient algorithms which are faster in practice (mostly because they use sequential access).
Question for anyone that consumes a lot of PDFs as I do: what do you use instead? Manual data insertion is an absolute no. So that leaves the Zotero alternatives, but quick search shows 0 mentions for any of them too.
Structured Content sounds great, but we already have that: add a number to your video title.