This makes me want to end my Claude code subscription to be honest. Effective altruists are proving once again to be a bunch of clueless douchebags.
Yes these are good points and probably the most important ones as far as the maths is concerned, though I would say regularisations methods are really standard things one learns in any ML / stat course. Ledoit, Wolf…
No, sorry but that’s a very dumb way to think about it. If someone can get something done in half the time it takes someone else, and is slacking off the rest of the time, is he stealing from the company ? Obviously…
I think type hints have mostly changed Python for the better but I still get frustrated by the number of half baked features and inconsistencies in the language. You end up fighting quirks ( like isinstance not working…
I’ve been disappointed with Jax which I was trying to use for backward auto differentiation. The issue is that XLA JIT compilation is very slow and easily adds half a minute of overhead to the first call of the base…
This makes me want to end my Claude code subscription to be honest. Effective altruists are proving once again to be a bunch of clueless douchebags.
Yes these are good points and probably the most important ones as far as the maths is concerned, though I would say regularisations methods are really standard things one learns in any ML / stat course. Ledoit, Wolf…
No, sorry but that’s a very dumb way to think about it. If someone can get something done in half the time it takes someone else, and is slacking off the rest of the time, is he stealing from the company ? Obviously…
I think type hints have mostly changed Python for the better but I still get frustrated by the number of half baked features and inconsistencies in the language. You end up fighting quirks ( like isinstance not working…
I’ve been disappointed with Jax which I was trying to use for backward auto differentiation. The issue is that XLA JIT compilation is very slow and easily adds half a minute of overhead to the first call of the base…