Assertion: gradient descent | /r/HasProperty | bgd
Facets:
Source sentences:
text: Batch Gradient Descent (BGD)
text: Batch gradient descent (BGD): calculate the error for each example in the training dataset, but only updates the model after all training examples have been evaluated.
text: What is Batch Gradient Descent (BGD)?
text: Batch gradient descent (BGD) computes the gradient using the whole dataset.
text: Batch Gradient Descent (BGD)
text: One form is called Batch Gradient Descent (BGD).
text: One is called batch gradient descent (BGD) and the other is stochastic gradient descent (SGD).
text: The basic difference between batch gradient descent (BGD) and stochastic gradient descent (SGD), is that we only calculate the cost of one example for each step in SGD, but in BGD, we have to calculate the cost for all training examples in the dataset.