  Machine learning has now become an integral part of research and innovation.
The field of machine learning density functional theory has continuously
expanded over the years while making several noticeable advances. We briefly
discuss the status of this field and point out some current and future
challenges. We also talk about how state-of-the-art science and technology
tools can help overcome these challenges. This draft is a part of the "Roadmap
on Machine Learning in Electronic Structure" to be published in Electronic
Structure (EST).
