LM101-036: How to Predict the Future from the Distant Past using Recurrent Neural Networks episode artwork

EPISODE · Sep 28, 2015 · 25 MIN

LM101-036: How to Predict the Future from the Distant Past using Recurrent Neural Networks

from Learning Machines 101

In this episode, we discuss the problem of predicting the future from not only recent events but also from the distant past using Recurrent Neural Networks (RNNs). A example RNN is described which learns to label images with simple sentences. A learning machine capable of generating even simple descriptions of images such as these could be used to help the blind interpret images, provide assistance to children and adults in language acquisition, support internet search of content in images, and enhance search engine optimization websites containing unlabeled images. Both tutorial notes and advanced implementational notes for RNNs can be found in the show notes at: www.learningmachines101.com .

Episode metadata supplied by the publisher feed · Published Sep 28, 2015

Embed this episode

NOW PLAYING

LM101-036: How to Predict the Future from the Distant Past using Recurrent Neural Networks

0:00 25:26

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

Frequently Asked Questions

How long is this episode of Learning Machines 101?

This episode is 25 minutes long.

When was this Learning Machines 101 episode published?

This episode was published on September 28, 2015.

Can I download this Learning Machines 101 episode?

Yes. Use the download control on the episode player to save the publisher-provided media file.
URL copied to clipboard!