Last month, we found seven time-series datasets over at https://machinelearningmastery.com/time-series-datasets-for-machine-learning. They start simple and small, getting larger and more complex towards the end. We began by pushing the first datasets into Kaggle to explore and prepare the data.
Will, one of our attendees, suggested Facebook's Prophet library https://facebook.github.io/prophet/docs/quick_start.html as a way to get started with making predictions from this kind of data.
The optional homework is to see what you can predict from the Australian Minimum Daily Temperatures dataset, which we've uploaded to Kaggle for convenience https://www.kaggle.com/paulbrabban/daily-minimum-temperatures-in-melbourne. You don't have to use Prophet, but if you want to it's available on Kaggle R and Python kernels.
Catch up with the group on the SheffieldML slack channel https://sheffield.digital/slack, channel #shef_ml and follow us on Twitter https://twitter.com/shef_ml
You'll need a laptop (or to buddy up with someone else!). If you'd like to use Kaggle (which provides online notebooks in Python and R) then please sign up for an account at https://www.kaggle.com beforehand.
Thanks to Sheffield Technology Parks for our venue (all they ask is that you leave them a review on Google Maps) and to Razor https://www.razor.co.uk for sponsoring this meetup group.
Want more AI and Machine Learning? Check out the first AI Tech North conference - Leeds, July 2019. More info and tickets at https://www.aitechnorth.uk/ai-tech-north-2019