Examples of using The neural network in English and their translations into Indonesian
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                        Ecclesiastic
                    
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has a proprietary LG Neural  Engine which better enables it to mimic the neural network of the  human brain.
The neural network analyzes the  dataset, and then a cost function tells the neural network how far away it was from the  target.
where it is processed by the neural network to improve the  image quality.
From this data, the neural network cobbled together a predictive model of the  likelihood that a patient suffered from schizophrenia based on the  blood flow.
The neural network analyzes the  data set,
The neural network just did better," says lead author Dr Phoebe DeVries,
I finally got the neural network online, so when my brain tells the  gauntlet to wave.
Like the  brain, the neural network uses a series of nodes interconnected by stimulating specific centers needed to complete a task.
Next, they fed the neural network data showing how the  mainshock changed the  stress level at the  center of each surrounding cell.
These images the neural network has not seen before and is not programmed to remember during the  game.
But the neural network slowly learns;
In this example, the neural network has been trained to distinguish between valid
failed both to disengage from the  interruption and to reestablish the neural network associated with the  disrupted memory.
Reinforced learning: In this algorithm, the neural network is reinforced for positive results, and punished for a negative result, forcing the neural network to learn over time.
The neural network is strengthened in this algorithm for favorable outcomes and punished for adverse outcomes, forcing the neural network to learn over time.
Forward propagation of a training pattern's input through the neural network in order to generate the  propagation's output activations.
Once an input is presented to the neural network, and a corresponding desired or target response is set at the  output,
I suspect the neural network model has the  issue of"overfitting"(the phenomenon in neural network  where the  model is trained to fit only to the  small training dataset)
Such technology may become a panacea for monopolization and spamming as the neural network analyzes users behavior,
Makoto thus suspects the neural network model has the  issue of"overfitting"(the phenomenon in neural network  where the  model is trained to fit only to the  small training dataset),