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Sure, its like when the Quantnet C++ course made us write our own implementation of resizable arrays in the exercises. It was challenging and gave a glimpse of how its implemented in real world without getting into the weeds with amortization analysis etc. But we all use the std::vector object in real life as we know it is part of STL and just works out of the box.Actually a lot of parameter tuning is trial-and-error But its largely automated in ML libraries with gridsearch and pipelines which streamline your workflow a lot.
Sure, its like when the Quantnet C++ course made us write our own implementation of resizable arrays in the exercises. It was challenging and gave a glimpse of how its implemented in real world without getting into the weeds with amortization analysis etc. But we all use the std::vector object in real life as we know it is part of STL and just works out of the box.
Actually a lot of parameter tuning is trial-and-error But its largely automated in ML libraries with gridsearch and pipelines which streamline your workflow a lot.
