This journal club discusses data science papers and is open to all experience levels and specialities. Keeping up with the latest research and methods is important for data scientists and discussions with like-minded individuals are one of the best ways to do this.
Before each meeting, the organisers will choose one or more papers for that meeting from ones suggested by members. To start the meeting, the member then gives a short overview of the papers to spark discussion. It obviously helps if everyone has attempted to read the paper themselves beforehand but it’s not obligatory.
If you want to share your passion for a subject in a friendly environment, giving a presentation is an excellent way to do so. Just send a message to one of the organisers with details. Although many recent papers have been on deep learning, we would also welcome papers from a broader subset of data science and machine learning research or practice, e.g. causal inference, ethics, privacy or graphical models.
Historically the meetings have been in-person but since the covid-19 pandemic we have moved online and a proportion of our meetings may well continue online in the future too.