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Home Page: https://gt-coar.github.io/gt-coar-lab
License: BSD 3-Clause "New" or "Revised" License
An environment for interactive exploration of reinforcement learning
Home Page: https://gt-coar.github.io/gt-coar-lab
License: BSD 3-Clause "New" or "Revised" License
Add some use cases to README (or a docs/
site).
/dev/root 84G 52G 32G 62% /
linux-gpu-build/dev/root 84G 37G 47G 45% /
release/dev/root 84G 54G 30G 65% /
linux-gpu-testacme looks like an interesting addition:
A conda-forge staged recipes PR is open, but there on some snags for building some of its dependencies.
Pro:
Con:
ipydrawio 1.0.1 is up, and ready for integration.
conda-forge
conda-forge
packages (probably preferable)In CI, after building the installers, on fresh machines (without conda) attempt to run the installers, and use them to do some basic smoke tests:
atari_py
yet)Using conda-lock and mamba may give us better cacheability and reproducibility for these increasingly-large builds.
mamba
and conda-lock
to the base envdodo
to re-solve envs withconda-lock
, based on the state of environment.yml
Let's adopt a long-running poster
branch:
Have git HEAD
include
Link to the actual poster session:
master
poster
z2jh
, etc.dennybritz-2016 --+--- tensorflow
|---- scikit.learn
gh-pages
with jupyterliteUsing the embedded robotframework, selenium and firefox, test the functionality of gt-coar-lab:
Include an in-tool flashcard/spaced-repetition authoring and reviewing tool, with pre-built decks for the included notebook sets (#18).
After acquiring new skills and knowledge, the anki approach is effective at helping a learner retain the knowledge.
Build installers that come pre-packed with the GPU versions of key libraries, and necessary support packages.
Needed for:
dask.visualize
, etc.The sagemath stack is available from conda-forge
for osx and linux. It's probably worth exploring.
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