“Any good ML model is based on the right dataset. But how do you get high-quality labeled data without getting grey hair? Three speakers share real-world experiences of how they navigated figuring out what data were needed and finding strategic ways to get it.Speakers:Eric Navarro, Machine Learning Engineer at Radiobotics,”Fake it till you make it: Machine learning with sparse data.”Maria de Freitas, Growth Lead of Imagine Project, LEO Innovation Lab, “Using growth hacking to accelerate the accuracy of your ML models.”Akshay Pai, Co-founder and CTO, Cerebriu,”Handling radiology data: garbage in, garbage out.””

Price: Free

Link: https://www.meetup.com/aicopenhagen/events/259186876/