| data/hotel_data | ||
| data_preprocessing | ||
| evaluation_and_testing | ||
| recommenders | ||
| .gitignore | ||
| environment.yml | ||
| project_1_data_preparation.html | ||
| project_1_data_preparation.ipynb | ||
| project_2_recommender_and_evaluation.html | ||
| project_2_recommender_and_evaluation.ipynb | ||
| README.md | ||
Recommender Systems class - Project 2
Preparing your system
-
Install Docker.
-
Fork this repository to your GitHub account.
-
Run Jupyter docker image:
docker run \
-d -p 8888:8888 \
-v DIRECTORY:/home/jovyan/REK \
--name REK \
jupyter/minimal-notebook
Remember to change DIRECTORY to directory where all files can be found. You can change it to $(pwd) if your current directory is proper one.
- Get loging link with following command:
docker logs REK 2>&1 | grep -o 'http://127.0.0.1:8888.*' | tail -n1
Example output:
http://127.0.0.1:8888/?token=2bb816a4bc36a4bdbf64e0c9a89f336ae5404a01d15e442c
- Prepare conda environment:
docker exec REK bash -c "
conda env create --name rs-class-env -f /home/jovyan/REK/environment.yml;
python -m ipykernel install --user --name=rs-class-env"
- You can start/stop container whenever you want:
docker stop REK
docker start REK
If you want to start from scratch, you can remove container:
docker stop REK
docker rm REK
Now you are ready to work!