Science, Data, & Analytics 📊Data and number crunching, analysis and visualisation, machine learning, and how those things affect us human beings.
We are currently reviewing the submissions for the Science, Data, & Analytics track.
Hear more about Science, Data, & Analytics from the track organisersWatch the PyConline AU Stream for Science, Data, & Analytics: What should excite you about the Science, Data, & Analytics track?
There are so many directions that this track can take. There is always technical talks about explicit packages, but there's also talks about core concepts like privacy and data security.
We don't want talks just from the experts, we want talks from newer people about their experience, we want to hear from scientists using data.
We want to hear about deep learning, machine learning, interactive dashboards; processes and how you get data and how you present data in a way that stakeholders can understand it; policies, and what we should think about when it comes to data.
Need help with your submission? Check our CFP for mentorship details.