Deep Learning in the Sciences

In this episode of the Data Exchange I speak Bharath ("Bart") Ramsundar, author and open source developer. While in graduate school, Bart created DeepChem, an open source project that aims to democratize deep learning for science. DeepChem historically was developed for researchers in the life sciences, so the working examples in its tutorials draw from areas like chemistry and bioinformatics. Researchers in other branches of science (e.g., physics and astronomy) have long embraced machine learning and big data management systems. In fact, I remember that during the early days of Hadoop and MPP databases, creators and vendors of big data systems approached research labs known to possess massive amounts of data.