jasonmarks_
Joined 4 years ago
Joined 4 years ago
Whattttt? This is bad behavior on your part as a redistributor. It is more polite to do a bulk download (NDFD) and iterate against that directly.
The fact that error correction seems to be struggling implies unaccounted for noise that is not heat. Who knows maybe gravitational waves heck your setup no matter what you do!
pywgrib https://www.cpc.ncep.noaa.gov/products/people/lxu/cookbook/a... containerized https://hub.docker.com/repository/docker/jmarks213/container...
I am not familiar with those books or their content but that definitely reads as if the intent has been substantially changed. A typo 100 years ago might have been a letter off in the type setter; the typos these days are rewrites!
This is unacceptable. Typo's are not just aggravating but as they accumulate they begin to veer towards mutating the authors original intent.
Two critiques: - Kindle would be a much better product if kindle.amazon.com took me to a dedicated UX that is not washed out by the e-commerce bloat that currently surrounds it. - You have to carefully purchase Kindle editions of books. There are definitely Kindle edition books for sale that are digitally scanned, imported, and compiled as a Kindle edition with no proof reading having occurred leaving you stuck with typo riddled messes.
Definitely. Training on the historical data creates compelling forecasts but it comes off as a magic box. Where are the missing physics for the high performance cluster?
You are a bit misleading here. The model is trained on historical data but each run off of new instrument readings will be generated a few times in an ensemble.
What do you mean?
It could very well be that it is less than optimal to compare lots intended for residential with lots you would develop a convenience store on.
That is one angle of view. Alternatively, you could be encouraging vacant lot (or equivalent structure) owners to sell if neighbors are improving properties while they are not.