canaus

Trying to understand the depth and necessity of labeling for an algorithm, specifically having people or other algorithms label and check the labeling of data.

Do the data sets need to be labeled extensively every time an algorithm needs to be trained? How often does a new data set need to be labeled, is it only with novel data?

When your team members are done with their sprint work, do they help with work on the tickets within the sprint or do they pickup items from the backlog?

What would you prefer?

I'm trying to find professional implementations of data structures and algorithms like trees, graphs, DFS, BFS, etc. I'm having trouble wrapping my head around when and why you'd utilize them.