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Notebooks inspired by "Deep Learning with Python by Francois Chollet" in TensorFlow 2.0 and Keras
Jupyter Notebook Shell
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data/preprocessed/dogs-vs-cats
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tasks/gc
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README.md
environment.yml
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README.md

Work with conda local env:

  1. Create conda env conda env create -f environment.yml
  2. Update env file conda update --all then conda env export --no-builds > environment.yml
  3. Update env file after installing some packages conda env update

Generate a requirements.txt file:

conda list -e > requirements.txt

Troubleshooting

  • In case the new kernel didn't show up in Jupyter, you can add it manually python -m ipykernel install --user --name keras

Work with virtualenv

Create a new env

virtualenv -p python3 .venv

Install a Jupyter kernel

ipython kernel install --user --name=.venv

Activate the env

source .venv/bin/activate

Deactivate the env

deactivate

Enable jupyter lab git extension:

$ jupyter labextension install @jupyterlab/git
$ jupyter serverextension enable --py jupyterlab_git
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