The point is that when you're using a neural network library, such as Microsoft CNTK or Google TensorFlow, exactly how L1 regularization is implemented can vary. This means an L1 lambda that works ...

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch.

Dynamic graphs: Gluon enables developers to define neural network models that are dynamic, meaning they can be built on the fly, with any structure, and using any of Python’s native control flow.

Sony's R&D Platform and System R&D Group have used these core libraries as a base for products and services that incorporate deep learning. These include AR Effect, a SmartAR (augmented reality ...

At version r1.5, Google's open source machine learning and neural network library is more capable, more mature, and easier to learn and use ...

In many scenarios, using L1 regularization drives some neural network weights to 0, leading to a sparse network. Using L2 regularization often drives all weights to small values, but few weights ...