Description

Machine Learning is an effective tool that can and has been used in high-stakes decision-making. Thereby, automated decision making based on ML tools with effects on individuals and the society demands better understanding of them (ML tools) and their behaviours. Can black box models cater to that demand? Can we trust them and if yes, how much? This tutorial is aimed to (I) introduce the models/methods for explainability of Machine Learning models (ii) provide hands-on in tools for the same and (iii) discuss prospects of applications of mentioned methods. This tutorial will especially be useful for industry professionals, researchers, policy makers, postgraduate and undergraduate students seeking further research on this topic. Resource Persons: Dr Kasun Amarasinghe, Carnegie Mellon University Pittsburgh PA, USA Dr Damayanthi Herath, Department of Computer Engineering, University of Peradeniya, Sri Lanka Eng. Shyaman Jayasundara, Agricultural Biotechnology Centre, University of Peradeniy Eng. Amila Indika, Department of Computer Engineering, University of Peradeniya, Sri Lanka Coordinated by: Dr. Damayanthi Herath