A collection of various Jupyter Notebooks related to machine learning and data science in general.

├── Makefile   <- Makefile with commands like `make data` or `make train`
├── README.md  <- The top-level README for developers using this project.
│
└── notebooks  <- Jupyter notebooks directory.

Here we will document the different make commands defined in the Makefile. All commands (excluding the all command which is simply executed by running make) are executed by the following format: make [COMMAND]. To see the contents of a command that will be executed upon invocation of the command, simply run make -n [COMMAND].

• all: (aka: make) alias for jupyter command
• jupyter: launches the Jupyter notebook development Docker image
• containers: launch all Docker containers
• list-containers: list all running containers
• stop-containers: simply stops all running Docker containers
• restart-containers: restart all containers
• clear-nb: simply clears Jupyter notebook output
• clean: combines all clearing commands into one

This is the same Docker command that is defined in the Makefile as the jupyter command. To run it outside of make, first git clone the repo:

git clone https://github.com/RagingTiger/MiscNB.git

Then cd MiscNB and run the following:

docker run -d \
           --rm \
           --name misc_nb \
           -e JUPYTER_ENABLE_LAB=yes \
           -p 8888 \
           -v $PWD:/home/jovyan \
           ghcr.io/ragingtiger/omega-notebook:master && \
sleep 5 && \
  docker logs misc_nb 2>&1 | \
    grep "http://127.0.0.1" | tail -n 1 | \
    sed "s/:8888/:$(docker port misc_nb | \
    grep '0.0.0.0:' | awk '{print $3'} | sed 's/0.0.0.0://g')/g"

Click the link (should look similar to: http://127.0.0.1:RANDOM_PORT/lab?token=LONG_ALPHANUMERIC_STRING) which will automatically log you in and allow you to start running the notebooks.

Project based on the cookiecutter data science project template. #cookiecutterdatascience