title: How total loss is manipulated in mini batch gradient descent as the loss function is calculated and minimized for mini batches?
body: <p>In mini batch GD, the loss function is calculated for mini batches. Suppose we have 480 training example and the batch size is 32. So there will be 480/32= 15 loss function. In every batches these 15 loss function will be minimized by updating the weights and bias. But how do we accumulate the total loss function using those 15 different loss function. Please correct me if my understating is not correct.</p>