Machine Learning for Drug Discovery

This repository contains all code and examples used in the ACS in focus book Machine Learning for Drug Discovery.

Using this repo

All code was prepared to be executed in a Python environment. For the reader's convenience, we provide a Conda environment file that can be used to create a python environment with previously selected and tested packages.

To install Conda in your system, please refer to Conda's installation guide.

After Conda ins installed and ready, navigate to the conda_env folder and execute the following command to create the environment:

conda env create -f environment_ML_Env.yml

Now activate your environment with:

conda activate environment_ML_Env

And you will be ready to initialize the Jupyter notebook form the parent folder using:

jupyter notebook