tech_ml_an_co
tech_ml_an_co t1_istpcr1 wrote
Ohh cs interview processes are so broken, ml is not different. I really don't know why that happened. I just recently had a leetcode interview as a lead ml engineer. I mean seriously, I can guarantee that I was able to solve that when I finished my degree 10 years ago. But today why should I invest my free time into leetcode, instead of learning something useful?
tech_ml_an_co t1_izt4bd0 wrote
Reply to What’s different between developing deep learning product and typical ML product? by digital-bolkonsky
Quite different tech stack for APIs. DL requires some kind of model server with GPU. For traditional ML use Lambda or FastAPI on a server.
For batch processing it's more similar, depending on your data size, you might not need a GPU even for Deep learning.
Also deep learning is usually unstructured data, which requires different storage and training infrastructure.
You can read books about that topic however at the core that's the difference a that's why a lot of companies still don't utilize DL.