APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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One epoch
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One batch
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One iteration
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None of the above
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Detailed explanation-1: -Epochs. One Epoch is when an ENTIRE dataset is passed forward and backward through the neural network only ONCE. Since one epoch is too big to feed to the computer at once we divide it in several smaller batches.
Detailed explanation-2: -Forward pass is a technique to move forward through network diagram to determining project duration and finding the critical path or Free Float of the project. Whereas backward pass represents moving backward to the end result to calculate late start or to find if there is any slack in the activity.
Detailed explanation-3: -One epoch means that each sample in the training dataset has had an opportunity to update the internal model parameters. An epoch is comprised of one or more batches. For example, as above, an epoch that has one batch is called the batch gradient descent learning algorithm.
Detailed explanation-4: -In the context of Neural Networks iteration is forward and backward pass. Then, in each epoch, there will be 5 batches (20/4=5). Each batch will be passed by the algorithm there will be 5 iterations per epoch.