Hey all,
Context
I’ve taken the math for ML and datascience and I’m now busy with machine learning specialisation. The theme that keeps coming back is that deep learning surpasses model ‘quality’ compared to traditional ML given that there is enough data.
Discouragement Problem
But when I start brainstorming about deep learning projects I allways feel discouraged when I think about how on earth do I collect the right data and even more discouraged when I think about how to get the right amount of data.
Question
Does anyone have any good books/courses to get inspired about data collection?
Bonus points if source goes beyond the financial IT services industry that is bloated with data.
Thanks!