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Can anyone tell me what is epoch and batch in Deep Learning?

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In Deep Learning, epoch means the total dataset is passed forward and backward in a neural network once. Since one epoch will be large to feed to the neural network at once, we have to divide it into multiple batches.

Batch size in Deep Learning refers to the number of training examples utilized for each iteration. We have to adjust this batch size according to our machine’s computational power.

Suppose, we have 2000 training examples we are going to train on.

We can split the dataset into batches of 500 and then it will take 4 iterations for one epoch. 

You can watch this video to know more:

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