Conversation on Turing Course - An Introduction to Transparent Machine Learning
This is a conversation with Lily Clements on our course "An Introduction to Transparent Machine Learning", freely available at https://pykale.github.io/transparentML/ to enable learners of diverse backgrounds to understand and apply transparent machine learning with confidence and trust.
This course aims to address the priority of transparency in responsible AI. We will study both transparent machine learning systems/models and transparent machine learning processes. We will adapt classical machine learning textbooks and materials under this framework to give a fresh treatment that will be more accessible for learners from multiple disciplines, including engineering, science, social sciences, medical science, and humanities. This will greatly complement the existing Responsible AI training landscape in the UK and beyond.
Specifically, this course will recast selected contents in a leading textbook into the perspective of system and process transparency under a recent AI transparency framework from the Alan Turing Institute on "AI in Financial Services". Transparent machine learning systems will cover fully transparent machine learning models such as linear regression and "semi-transparent" machine learning models such as deep learning. Transparent machine learning processes will cover machine learning model evaluation and software development methodologies such as cross validation and software development life cycle.