I don't see why electric motors are not backdriveable enough. Boston Dynamics' Spot uses electric motors with harmonic drive gearboxes (or some other backdriveable transmission) as an example of this. Similarly, series…
It's bonded by epoxy just like plywood is. Technically plywood is a composite (at least from a mechanical engineering perspective).
As someone with a similar background, I believe some of the confusion is because there is a lot of overlap. System identification is very similar to supervised learning, however there are other learning "methods" that…
I'd don't know what you mean by "performs like" but it's definitely significantly closer in runtime speed after the first run to compiled languages than interpreted (in particular Python/Matlab). Anyways, my point was…
I don't know about other languages, but in Julia I've heard people often say that loops end up faster than the equivalent vectorized code. So while this is true for Python/Matlab I don't think it is good universal…
I don't see why electric motors are not backdriveable enough. Boston Dynamics' Spot uses electric motors with harmonic drive gearboxes (or some other backdriveable transmission) as an example of this. Similarly, series…
It's bonded by epoxy just like plywood is. Technically plywood is a composite (at least from a mechanical engineering perspective).
As someone with a similar background, I believe some of the confusion is because there is a lot of overlap. System identification is very similar to supervised learning, however there are other learning "methods" that…
I'd don't know what you mean by "performs like" but it's definitely significantly closer in runtime speed after the first run to compiled languages than interpreted (in particular Python/Matlab). Anyways, my point was…
I don't know about other languages, but in Julia I've heard people often say that loops end up faster than the equivalent vectorized code. So while this is true for Python/Matlab I don't think it is good universal…