This repo contains code from various posts from the Practical Cheminformatics blog
conda create -n qsar python=3.9
conda activate qsar
pip install rdkit pandas datamol molfeat scikit-learn numpy yellowbrick jupyterThe molskill directory contains the code for the post "Getting Inside the Mind of the Medicinal Chemist with Machine Learning"
pip install rdkit pandas seaborn scikit-posthocs
conda install molskill -c msr-ai4science -c conda-forge
For more information on MolSkill see the the molskill git repo
The counterfactuals directory contains code for the post "Using Counterfactuals to Understand Machine Learning Models"
conda install pip python=3.9
pip install rdkit PyTDC useful_rdkit_utils tqdm scikit-learn numpy<1.24 seaborn exmol pandas mols2grid crem
Thanks to Mary Pittman for the installation note
Please see README.md in the solubility directory