This is the code for this video series: https://www.youtube.com/watch?v=nAEb1lOf_4o

You will need rdkit to run this code.

Follow these instructions to install rdkit. https://www.rdkit.org/docs/Install.html

If you run on Ubuntu / WSL you can simply run:

sudo apt-get install python-rdkit

Ideally execute the code in an anaconda environment, that's the easiest solution with rdkit.

For pytorch geometric follow this tutorial: https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html

Make sure your CUDA version as well as torch version match the PyG version you install. I've used torch 1.6.0 as it seemed to be most stable with the other libraries.

• Its highly recommended to setup a GPU (including CUDA) for this code.
• Here is where I found ideas for node / edge features: https://www.researchgate.net/figure/Descriptions-of-node-and-edge-features_tbl1_339424976
• There is also a Kaggle competition that used this dataset (from a University): https://www.kaggle.com/c/iml2019/overview

It is required to use conda for this setup, e.g.

wget https://repo.continuum.io/archive/Anaconda3-5.3.1-Linux-x86_64.sh

You need to start the following things:

• Streamlit server

streamlit run dashboard.py

• MlFlow Server

mlflow server \
    --backend-store-uri sqlite:///mlflow.db \
    --default-artifact-root ./artifacts \
    --host 0.0.0.0
    --port 5000

• MlFlow served model

export MLFLOW_TRACKING_URI=http://localhost:5000
mlflow models serve -m "models:/YourModelName/Staging" -p 1234

TODO: Check if multi-input models work for MLFLOW!!!