I'm using this repo to compliment my blog (briansigafoos.com) as I explore Machine Learning:
Install Python using mamba. Anywhere you see instructions for conda, you can use mamba instead (it's faster). Why not pip? If you're doing ML, mamba/conda makes it easier to have everything you need (including Python), and to optimize packages for your GPU.
# First:
# Install mamba for your machine: https://github.com/conda-forge/miniforge#mambaforge
# Or use this script: https://github.com/fastai/fastsetup/blob/master/setup-conda.sh
# Packages
mamba install -y -c fastchan \
jupyter \
ipywidgets \
notebook \
numpy \
pandas \
pytorch \
fastai \
graphviz \
psycopg2 \
python-dotenv- Install black
pip install black+pip install 'black[jupyter]' - Install [pre-commit]
pip install pre-commitandpre-commit install; touch .pre-commit-config.yaml
From kaggle.com > My Account > Create new API token to download credentials in kaggle.json.
mkdir -p ~/.kaggle
mv ~/Downloads/kaggle.json ~/.kaggle/kaggle.json
chmod 600 ~/.kaggle/kaggle.json- Update pre-commit hooks using
pre-commit autoupdate
- Add black and configure for VSCode
- Add VSCode tasks to autoformat code
- Add pre-commit hooks
- Add Github Action to run linters
- Add isort to auto-sort imports