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laprika0 OP t1_ium613q wrote

Thanks. You differentiate ML from DL. Can you say what you mean by that in this context? Is working with DL a different experience than working with e.g. probabilistic modelling? Or do you mean e.g. tensorflow, pytorch, jax vs pandas, numpy, scikit-learn?


TheDeviousPanda t1_ium7iy4 wrote

Scikit learn numpy pandas xgboost etc, totally fine to do on CPU which is great on MacBooks. Pytorch tensorflow jax? Forget it. If anyone in lab asks for help debugging on their local machine bc cluster is down, I just ignore it. Impossible to do prototyping on Mac.


suflaj t1_ium7xcv wrote

ML is a superset of DL. It's very different working on those two, almost like most ML rules and theory straight up do not apply to modern DL.