> Whenever I teach people time series forecasting, I always point out that one of the biggest challenges is that you will always have values at prediction time that are out side the range of values observed during training (specifically the value of t).
I don't get this, time is usually not a covariate in ts models, so why is it a challenge?
Exactly, girls and women can do astonishing work in fields that favour more or less their mutual traits and vice versa, no need for "hehe we are better because GPA said so".
I love the typical family-owned small businesses, their runners are the ones that aspired entrepreneurs should listen to their advices instead of bestsellers books of ghouls preaching their bullshit.
This is a bad case of whataboutism (I hate this word but it describes the answer you gave), what do you mean by accelerating understanding? Maybe they are good as suggestion engines, but it is very early to state what you did.
This is actually the truth, we all have tens or hundreds of priceless saved links. However, I claim that 90% are forgotten after a day or two, maybe that's actually something that small language models can fix ?
I don't get this, time is usually not a covariate in ts models, so why is it a challenge?