Long time ago in a GPU far-far away, the deep learning rebels are happy. They have created new ways of working with chemistry using deep learning technology
Master your molecule generator: Seq2seq RNN models with SMILES in Keras
UPDATE: Be sure to check out the follow-up to this post if you want to improve the model: Learn how to improve SMILES based molecular autoencoders with
SMILES enumeration and vectorization for Keras
The SMILES enumeration code at GitHub has been revamped and revised into an object for easier use. It can work in conjunction with a SMILES iterator object
Learn how to teach your computer to "See" Chemistry: Free Chemception models with RDKit and Keras
The film Inception with Leonardo Di Caprio is about dreams in dreams, and gave rise to the meme “We need to go deeper”. The title has also
A deeper look into chemical space with neural autoencoders
In the last blogpost the battle tested principal components analysis (PCA) was used as a dimensionality reduction tool. This time we’ll take a deeper look into chemical