Jupyter Notebooks and some Python code related to machine learning
A Binder-compatible repo with an environment.yml file.
Binder will search for a dependency file, such as requirements.txt or environment.yml,
in the repository's root directory .
The dependency files will be used to build a Docker image for the notebook.
If an image has already been built for the given repository, it will not be rebuilt. If a new commit has been made, the image will automatically be rebuilt.
Notes
The environment.yml file should list all Python libraries on which your notebooks depend, specified as though they were created using the following conda commands:
source activate example-environment
conda env export --no-builds -f environment.yml
Note that the only libraries available to you will be the ones specified in the environment.yml, so be sure to include everything that you need!
Also note that conda will possibly try to include OS-specific packages in environment.yml, so you may have to manually prune environment.yml to get rid of these packages.
Confirmed Mac-OSX-specific packages that should be removed are:
libcxxabi=4.0.1
appnope=0.1.0
libgfortran=3.0.1
libcxx=4.0.1
Confirmed Windows-specific packages that should be removed are:
m2w64-gcc-libgfortran=5.3.0
m2w64-gcc-libs=5.3.0
m2w64-gcc-libs-core=5.3.0
m2w64-gmp=6.1.0
m2w64-libwinpthread-git=5.0.0.4634.697f757
msys2-conda-epoch=20160418
pywinpty=0.5.5
vc=14
vs2015_runtime=14.0.25420
wincertstore=0.2
winpty=0.4.3