New blog post is up introducing the new MoleculeNet API and the importance of ML benchmarks.
Benchmark datasets are an important driver of progress in machine learning. Unlike computer vision and natural language processing, the diversity and complexity of datasets in chemical and life sciences make these fields largely resistant to attempts to curate benchmarks that are widely accepted in the community. In this post, we show how to add datasets to the MoleculeNet benchmark for molecular machine learning and make them programmatically accessible with the DeepChem API.