Team: Runtime Terror
The project contains the following methods, runnable as self-contained and independent Jupyter notebooks, for collaborative filtering:
- The baseline solution - SVD + ALS on a normalized dataset (notebook).
- The baseline solution with a k-NN initialization approach (notebook).
- The baseline solution with a Gaussian processes approach (notebook).
- Improved SVD (notebook).
- The baseline solution with Improved SVD (notebook).
- Neural Net for Collaborative Filtering (notebook).
- Sparse FC (notebook).
- Knowledge Graphs (notebook).
- ...
- Start by creating a virtual environment. Using conda,
conda create --name cil_runtime_terror python=3.6.13
- Activate the virtual environment. Using conda,
conda activate cil_runtime_terror
- Go to the project root and install the dependencies.
pip install -r requirements.txt