Really?
Were you around during the dotcom era?
Although I'm not old enough, I've heard that OR in the 80s was the same crap.
1,229 karma · joined June 5, 2015
Were you around during the dotcom era?
Although I'm not old enough, I've heard that OR in the 80s was the same crap.
We are at the inflection point where they are all about to crash and burn. Good riddance.
Well, yeah, for something so rudimentary. Use a library. Nothing to see here.
Convex optimization is also useful if you care about optimizing convex functions. Which I bet you do.
Yep. You'll end up with a lopsided allocation, with one or two allocations holding a very large percentage of the total allocation.
Distributing the allocation weights could help, e.g. with ensembling, regularization or some other kind of penalty.
This is a basic LP problem that you'll come across in a textbook.
I also doubt that it's optimal. An implementation using Hierarchical Risk Parity for instance would be more interesting. I assume you can model risk/uncertainty here.
By the way, Google has an OR tools framework that implements these kind of solvers for you:
It's already a huge pain dealing with know-nothings inside of tech firms. Now imagine having to cater to know-less-than-nothings somewhere else.
There are tons of software "engineers" who try to escape fintech for FAANGs or even startups, coming from top tier firms like Goldman and McKinsey.
Likewise, bioinformatics generally pays a lot less than traditional SWE roles.
So what I have seen is the exact opposite in practice: people with minimum coding skills in other fields trying to jump into tech firms.
Now all of the infrastructure is built. Oversaturated and consolidated.
At least the game dev scene is vibrant, even if overcrowded.
Your tech talks are also awesome.
The Internet used to be about building and sharing things. Then it turned into a giant and mindless message feed where everyone exposes everything about their private lives, intentionally or not.
Now all of the hot new opportunities that exist are to spy on and exploit that data. The latest AI hype is a consequence of the pervasiveness of "big data".
I miss building and sharing cool things instead with the online community.
You are a genius and a god among us. Thank you for making the deepest and most beautiful games I have ever enjoyed.
There are only five patterns that matter in real world software development.
Observable
Singleton
Composition
MVC
Inversion of Control
And the last one isn't even covered by GOF. The book is an out of date relic of 90s programming. Let it die already.
There are much better books to learn algorithms from. Even Elements of Programming Interviews is better.
It is worth coming back to if you want to read proofs to understand things in depth. But it is terrible as a fundamental instructive text.
And I am surprised no one mentioned Operating System Concepts (the dinosaur book).
It was the most useful CS text I read in college. I see a lot of SICP love; I never had it for a college course, but it looks good as well.
One easy fix. Send a verification email to users when a different device is detected before allowing log in.
I mean, even Steam does this.
100 vs 140 will be a very strong indicator. 100 vs 110 will not; I would not trust 110 to yield a better outcome 80-90% of the time, as GP claimed.
Which is why the comparison of IQ scores at that coarseness is plain silly.
That wasn't the point. I would say the same for 100 and 110.
Some MENSA members in this thread seem very attached to their scores.
Most of modern ML just extends convex optimization techniques anyway.