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

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

FromLearning Machines 101


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

FromLearning Machines 101

ratings:
Length:
25 minutes
Released:
Sep 28, 2015
Format:
Podcast episode

Description

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 .
Released:
Sep 28, 2015
Format:
Podcast episode

Titles in the series (85)

Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions which will be addressed in the podcast series Learning Machines 101.