Commit graph

5 commits

Author SHA1 Message Date
Starbeamrainbowlabs 0b31c9e700
log start time, end time, and elapsed
just in case...!
2023-01-16 17:30:20 +00:00
Starbeamrainbowlabs 28a3f578d5
update .gitignore 2022-08-04 16:49:53 +01:00
Starbeamrainbowlabs b53c77a2cb
index.py: call static function name run 2022-07-26 19:51:28 +01:00
Starbeamrainbowlabs dac6919fcd
ai: start creating initial scaffolding 2022-07-25 19:01:10 +01:00
Starbeamrainbowlabs 8a9cd6c1c0
Lay out some basic scaffolding
I *really* hope this works. This is the 3rd major revision of this
model. I've learnt a ton of stuff between now and my last attempt, so
here's hoping that all goes well :D

The basic idea behind this attempt is *Contrastive Learning*. If we
don't get anything useful with this approach, then we can assume that
it's not really possible / feasible.

Something we need to watch out for is the variance (or rather lack
thereof) in the dataset. We have 1.5M timesteps, but not a whole lot
will be happening in most of those....

We may need to analyse the variance of the water depth data and extract
a subsample that's more balanced.
2022-05-13 19:06:15 +01:00