A big part of AI and Deep Learning these days is the tuning/optimizing of the algorithms for speed and accuracy. Much of today’s deep learning algorithms involve the use of the gradient descent ...

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 ...

In this video, we will understand in detail what is Momentum Optimizer in Deep Learning. Momentum Optimizer in Deep Learning is a technique that reduces the time taken to train a model. The path of ...

In this course, you’ll learn theoretical foundations of optimization methods used for training deep machine learning models. Why does gradient descent work? Specifically, what can we guarantee about ...

At the end of the concrete plaza that forms the courtyard of the Salk Institute in La Jolla, California, there is a three-hundred-fifty-foot drop to the Pacific Ocean. Sometimes people explore that ...

A team of researchers led by Yumin Dong of Chongqing Normal University has developed a novel method to optimize parametric quantum circuits, a critical component of variational quantum algorithms. The ...