What exactly are we trying to accomplish? Will the new model architecture really be a game-changer? How much impact will this new dataset have on the model accuracy? These are some questions a typical machine learning team deals with on a daily basis. But it is important to not get bogged down by the intricacies, and always go back to the first principles approach. With the pace at which new research papers are pouring in, it is important for ML/Data/CV Scientists to sometimes take a back seat and think about the overall picture a bit more.

If we start off…

VisionCanary

Computer vision engineer; excited about building products and companies; ksaluja15.github.io

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