A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

A distributed compute and database platform for quantum chemistry.

A collection of QM data for training potential functions

Reweighted Autoencoded Variational Bayes for Enhanced Sampling (RAVE)

The Serenity Operating System 🐞

Calculate Root-mean-square deviation (RMSD) of two molecules, using rotation, in xyz or pdb format

aligning molecules

PyProt makes working with protein files very convenient. It supports popular protein structure file formats such as PDB and MOL2.

Cloud-based molecular simulations for everyone

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Just a quick example of how to use boost python

Programming Assignments and Lectures for Andrew Ng's "Machine Learning" Coursera course

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.