This is a project I undertook for the course project for the course "Deep Learning and Reinforcement Learning" offered by IBM Skills Network in May 2021
Simulations of molecular properties are computationally expensive. The purpose of this project is to use machine learning methods to come up with a model that can predict molecular properties from a database of simulations. If this can be done with high accuracy, properties of new molecules can be calculated using the trained model. This could open up many possibilities in computational design and discovery of molecules, compounds and new drugs.
The dataset is taken from Kaggle. Link to the dataset : Dataset