Our goal is to bring academics and practitioners together to study theoretical aspects of machine learning and the mathematical and statistical justification.
Our format during the meetup is to read through books, papers, articles etc. silently and after a few pages collectively discuss the material. We also do exercises and proofs together, at first silently everyone alone and then at the whiteboard together. It's all about gaining thorough understanding of the underlying theory to ML: Active participation is highly encouraged, including asking questions that deepen your understanding. There is no homework, but if you join in the middle of a chapter it's advisable that you get familar with the previous pages.
Although we are in the middle of a book, you can join at any time, as the chapters are very independent. The only requirement to succesfully do this is that you have a background in machine learning theory. A common way to achieve this is to having attended a course on Machine Learning.