From the docker
folder, run this command:
docker-compose up -d --build --remove-orphans
Then navigate to localhost:20000
to access the jupyter notebook.
Each folder in the src
directory is for a different ML task.
The purpose of this repository is for me to experiment with different ML tasks using one docker image having all dependencies installed.
https://www.kaggle.com/c/titanic/data OR kaggle competitions download -c titanic
https://www.kaggle.com/ngbolin/mnist-dataset-digit-recognizer/data
https://www.kaggle.com/shivamb/how-autoencoders-work-intro-and-usecases/data
Downloads the data when you run the script
Clone: [email protected]:learning1234embed/NeuralWeightVirtualization.git
Run: ./download_dataset.sh && python weight_virtualization.py -mode=a -network_path=mnist
Copy the contents of the mnist folder except the .py(c)
files