Visualization exploration for AI/XAI
Project description
Example application using trame for exploring MNIST dataset in the context of AI training and XAI thanks to XAITK.
Free software: BSD License
Installing
For the Python layer it is recommended to use conda to properly install the various ML packages.
macOS conda setup
brew install miniforge
conda init zsh
venv creation for AI
# Needed in order to get py3.9 with lzma
# PYTHON_CONFIGURE_OPTS="--enable-framework" pyenv install 3.9.9
conda create --name trame-mnist python=3.9
conda activate trame-mnist
conda install "pytorch==1.9.1" "torchvision==0.10.1" -c pytorch
conda install scipy "scikit-learn==0.24.2" "scikit-image==0.18.3" -c conda-forge
pip install -e .
Run the application
conda activate trame-mnist
trame-mnist
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
trame-mnist-1.0.0.tar.gz
(12.3 kB
view hashes)
Built Distribution
Close
Hashes for trame_mnist-1.0.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | eb3ef5d2bd2a47bb78ae0ef519ce0e7af030cf05d13f32d98a7c5355b26d156d |
|
MD5 | 0ed0a8ca96d9b068468a3fa818cf561c |
|
BLAKE2b-256 | f4b48947f170e24f52f2b260e2c2301630532d9cc53b37bf88e0ac6a25b0f3ef |