You're reading from Codeless Deep Learning with KNIME

Product typeBook

Published inNov 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781800566613

Edition1st Edition

Languages

Python

Tools

Knime

Concepts

Deep Learning

Authors (3):

Kathrin Melcher

KNIME AG

Rosaria Silipo

View More author details

Generating Free Text with RNNs

Now that we have seen how RNNs can be used for text classification, we can move on to the next case study. Here, we want to train an RNN to generate new free text in a certain style, be it Shakespearean English, a rap song, or mimicking a Brothers Grimm fairy tale. We will focus on the last application: training a network to generate free text in the style of Brothers Grimm fairy tales. However, the network and the process can be easily adjusted to produce a new rap song or a text in old Shakespearean English.

So, how can we train an RNN to generate new text?

The Dataset

First of all, you need a text corpus to train the network to generate new text. Any text corpus is good. However, keep in mind that the text you use for training will define the style of the text automatically generated. If you train the network on Shakespearean theater, you will get new text in old Shakespearean English; if you train the network on rap songs, you will get urban...

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Codeless Deep Learning with KNIME

Published in: Nov 2020Publisher: PacktISBN-13: 9781800566613

Authors (3)

Kathrin Melcher

Kathrin Melcher is a data scientist at KNIME. She holds a master's degree in mathematics from the University of Konstanz, Germany. She joined the evangelism team at KNIME in 2017 and has a strong interest in data science and machine learning algorithms. She enjoys teaching and sharing her data science knowledge with the community, for example, in the book From Excel to KNIME, as well as on various blog posts and at training courses, workshops, and conference presentations.
Read more about Kathrin Melcher

KNIME AG

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You're reading from Codeless Deep Learning with KNIME

Generating Free Text with RNNs

The Dataset

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