Where do you start with a machine learning problem? What are good algorithms and what techniques can you use to get good performance? This month, we're running a Kaggle session - we'll pick a problem or two and tackle them together.
If you're new to machine learning and keen to get started, check out the Titanic problem - www.kaggle.com - and predict who survives!
(You can find "kernels" - interactive notebooks that other people have written to solve the problem - to learn and help inspire your solutions. Here's a link to top-voted kernels for the Titanic problem, you'll find both R and Python available: www.kaggle.com)
We'll see who comes on the day and decide how to proceed. Maybe we'll decide to all work on one problem together, or split into smaller groups if we have different interests in the group. No question too basic, no technique too advanced.
It's an opportunity to practise and learn with other machine learning and AI enthusiasts. Let's see how well we can do!
You'll need a laptop if you want to participate in the challenge, and a Kaggle account will let you submit your solutions for scoring, as well as get you access to a powerful notebook of your own, avoiding the need to install software.
More details and tickets: www.meetup.com
Imported From: www.meetup.com
