Interpretable Machine Learning

1. This page provides some learning materials and notes for Interpretable Machine Learning and I would like to share my personal opinions on some papers.

2. The repository is organized as follows:

   • Introduction

     Discussion about the foundations of this topic : definition, intuition, motivation, evaluation

   • Notes

     My notes and understandings of papers in chronological order.

   • Materials

     Some related learning materials

   • Tags

     I would like to tag these papers with these notations

     • auxillary-model : Interprete a complex model with an interpretable one
     • self-interpretable : Design an self-interpretable structure on a complex model
     • human-experiment
     • proxy function
     • feature based
     • instance based
     • visualisation
     • ....

3. Any discussion and advice is welcome and many thanks.