Machine Learning (ML) is a popular topic in the research world. It has spread from basic computer science research to many other disciplines and RSEs are increasingly encouraged to be familiar with applying it to their projects.
In this talk I will discuss various limitations of ML, including how it can augment human bias, the problem with interpreting complex deep learning models and how real-world data can harm your model.
I'm an RSE at Microsoft Research in Cambridge. I work in the Deep Learning Engineering team in the ADA (All Data AI) group. I am also interested in diversity and inclusion in the technology sector.
