Jeremy Howard is co-founder of fast.ai, and researcher in residence on medical data science at the University of San Francisco. He is Chief Scientist at platform.ai, and held this role previously at doc.ai and Kaggle, where he was also President. Jeremy is a serial entrepreneur, having founded several successful companies after starting his career in management consulting. His most recent, Enlitic, was the first medical deep learning company, which just one year after its founding in 2014 had raised $15 million in two rounds of funding. He left the company two years after.
An open educator, Jeremy co-authored free courses on deep learning that have reached hundreds of thousands of learners around the world. He also co-authors an open-source library for deep learning called fastai, first released in 2018. The library sits atop PyTorch to provide a consistent interface for deep learning applications to images, text, time series, data frames and more. The second version of the library was announced in February this year with an arXiv preprint. All this work has recently come together as a book, written openly on Jupyter notebooks. Over the span of just a few years, he and fast.ai co-founder Rachel Thomas have done more to expand the reach and understanding of deep-learning technology than many global technology corporations.
Tuesday Oct. 13, 2020, 6:30 p.m.–Oct. 13, 2020, 7:30 p.m. in Data Science Applications, Enterprise Jupyter Infrastructure, Jupyter Community: Practices, Jupyter Community: Tools, Jupyter Core, Jupyter in Education, Jupyter in Scientific Research, JupyterCon Sponsor Talks