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 ...
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 ...
Dr. James McCaffrey of Microsoft Research explains stochastic gradient descent (SGD) neural network training, specifically implementing a bio-inspired optimization technique called differential ...
Optimization problems can be tricky, but they make the world work better. These kinds of questions, which strive for the best way of doing something, are absolutely everywhere. Your phone’s GPS ...
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 ...
The most widely used technique for finding the largest or smallest values of a math function turns out to be a fundamentally difficult computational problem. Many aspects of modern applied research ...
Deep Learning with Yacine on MSN
How to implement stochastic gradient descent with momentum in Python
Learn how to implement SGD with momentum from scratch in Python—boost your optimization skills for deep learning.
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