stochastic gradient descent

AI Deep Learning

Deep Networks Are Kernel Machines

Yannic Kilcher explains the paper “Every Model Learned by Gradient Descent Is Approximately a Kernel Machine.” Deep Neural Networks are often said to discover useful representations of the data. However, this paper challenges this prevailing view and suggest that rather than representing the data, deep neural networks store superpositions of the training data in their […]

Read More
Deep Learning TensorFlow

Keras Prerequisites – Getting Started with Neural Networks

deeplizard has put together a course on how to use Keras. In this course, we will learn how to use Keras, a neural network API written in Python! In this episode, we discuss the prerequisites required to start working with Keras, why Keras is a good library to learn, and what resources you’ll have available […]

Read More