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Using Python to Train a Deep Learning Architecture, It Just Keeps Getting Better
The longer we trained it, the better it got. It never hit asentot either, ore, never asentho to write. We would check it overnight. And wouldn't that lead to perfection though? The architecture still wasn't perfect at predicting its own future. But it just kept getting better with the same data set,. i'm even sure what the implications of that are, right? Right?