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Mini Batch Gradient Descent is an algorithm that helps to speed up learning while dealing with a large dataset. Instead of updating the weight parameters after assessing the entire dataset, Mini Batch ...

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Add a description, image, and links to the batch-gradient-descent topic page so that developers can more easily learn about it.

Abstract: The practical performance of stochastic gradient descent on large-scale machine learning tasks is often much better than what current theoretical tools can guarantee. This indicates that ...

Abstract: Mini-batch gradient descent (MBGD) is an attractive choice for support vector machines (SVM), because processing part of examples at a time is advantageous when disposing large data. Similar ...