We are interested in solving two infrastructural problems in data-centric fields such as machine learning: First, an inordinate amount of time is spent on preprocessing datasets, getting other people's code to run, writing evaluation/visualization scripts, with much of this effort duplicated across different research groups. Second, a only static set of final results are ever published, leaving it up to the reader to guess how the various methods would fare in unreported scenarios. I will present CodaLab Worksheets, a new platform which aims to tackle these two problems by creating an online community around sharing and executing immutable components called bundles, thereby streamlining the research process.Readings for this lecture
Percy Liang is a professor in the Department of Computer Science at Stanford. His research is in the area of machine learning and natural language processing.