project to retrieve and rank recommendations, built upon models and data written from the project: https://github.com/nking/recommender_systems.git
instructions: set up a virtual environment using conda or virtualenv with a python version that is >= 3.10.0
activate the virtual environment
to install the dependencies, the easiest way is to install this project: pip install --editable . else you can find the required libraries in pyproject.toml or setup.py
the unit tests show how to run the code.
Local testing:
pycharm:
using right click menu, mark the source tree directory:
src/main/python
using right click menu, mark the test tree directory:
src/test/python/movie_lens_retrieval
then pycharm tests will correctly resolve paths.
bash or other shell environment:
python and pytest can be used from the project's base
directory
Misc: the cold start, bayesian shrinkage could redone regularly. the code is in the reocmmendations project. could use for the "m" estimate of 0.75 quantile, data sketches like q-digest or t-digest on live data.