When Machine Learning Fails
Abstract
Machine learning can be used to examine a variety of challenges. However, this brings in a number of risks that can sometimes be overlooked leading towards a disastrous effect. We’ll discuss those risks and what you, as data scientists, can do to help mitigate them.
Event
Location
Virtual
Authors
Christopher Teixeira
(he/him)
Principal Data Scientist
My interests include using my skills for the public good and playing with baseball data.