Reader small image

You're reading from  Hands-On Mathematics for Deep Learning

Product typeBook
Published inJun 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781838647292
Edition1st Edition
Languages
Right arrow
Author (1)
Jay Dawani
Jay Dawani
author image
Jay Dawani

Jay Dawani is a former professional swimmer turned mathematician and computer scientist. He is also a Forbes 30 Under 30 Fellow. At present, he is the Director of Artificial Intelligence at Geometric Energy Corporation (NATO CAGE) and the CEO of Lemurian Labs - a startup he founded that is developing the next generation of autonomy, intelligent process automation, and driver intelligence. Previously he has also been the technology and R&D advisor to Spacebit Capital. He has spent the last three years researching at the frontiers of AI with a focus on reinforcement learning, open-ended learning, deep learning, quantum machine learning, human-machine interaction, multi-agent and complex systems, and artificial general intelligence.
Read more about Jay Dawani

Right arrow

Understanding RNNs

The word recurrent in the name of this neural network comes from the fact that it has cyclic connections and the same computation is performed on each element of the sequence. This allows it to learn (or memorize) parts of the data to make predictions about the future. An RNN's advantage is that it can scale to much longer sequences than non-sequence based models are able to.

Vanilla RNNs

Without further ado, let's take a look at the most basic version of an RNN, referred to as a vanilla RNN. It looks as follows:

This looks somewhat familiar, doesn't it? It should. If we were to remove the loop, this would be the same as a traditional neural network, but with one hidden layer, which we&apos...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Hands-On Mathematics for Deep Learning
Published in: Jun 2020Publisher: PacktISBN-13: 9781838647292

Author (1)

author image
Jay Dawani

Jay Dawani is a former professional swimmer turned mathematician and computer scientist. He is also a Forbes 30 Under 30 Fellow. At present, he is the Director of Artificial Intelligence at Geometric Energy Corporation (NATO CAGE) and the CEO of Lemurian Labs - a startup he founded that is developing the next generation of autonomy, intelligent process automation, and driver intelligence. Previously he has also been the technology and R&D advisor to Spacebit Capital. He has spent the last three years researching at the frontiers of AI with a focus on reinforcement learning, open-ended learning, deep learning, quantum machine learning, human-machine interaction, multi-agent and complex systems, and artificial general intelligence.
Read more about Jay Dawani