Trying to predict algorithmic inputs from data leads to a bottleneck, thanks to the uncertainties of the real world. Real-time data can be noisy. This noisy raw data has to be converted into scalar values (read: weights of neural network). The algorithm then uses these values to estimate output. In low data set-ups, such techniques…

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