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 ...
Artur is a copywriter and SEO specialist, as well as a small business owner. In his free time, he loves to play computer games and is glad that he was able to connect his professional career with his ...
Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative ...
Add a description, image, and links to the mini-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 ...