Do you have any ideas or guidance on how to do manual neural network optimization in the most systematic way? Especially when models train longer and the effects of hyperparameter fitting are very small, it's hard to stay on task and not lose the goal orientation. Iam using Tensorflow/Keras, callbacks like Tensorboard, EarlyStopping and ModelCheckpoint. Thanks a lot!


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