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

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Generating Product Names with RNNs

This last NLP case study is similar to the previous one. There, we wanted the network to create new free text based on a start sequence; here, we want the network to create new free words based on a start token. There, we wanted the network to create new sequences of words; here, we want the network to create new sequences of characters. Indeed, the goal of this product name generation case study is to create new names – that is, new words. While there'll be some differences, the approaches will be similar.

In this section, we will explore the details of this new approach.

The Problem of Product Name Generation

Normally, we don't associate artificial intelligence with creativity, as it is usually used to predict the outcome based on previously seen examples. The challenge for this case study is to use artificial intelligence to create something new, which is thought to be in the domain of creative minds.

Let's take...

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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 Product Names with RNNs

The Problem of Product Name Generation

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Authors (3)

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