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

Summary

This first chapter aimed to prepare you for the content provided in this book.

Thus, we started this chapter by reminding you of the importance of deep learning, as well as the surge in popularity it garnered following the first deep learning success stories. Such a surge in popularity is probably what brought you here, with the desire to learn more about practical implementations of deep learning networks for real use cases.

Nowadays, the main barrier that we come across when learning about deep learning is the coding skills that are required. Here, we adopted KNIME software, and in particular the open source KNIME Analytics Platform, so that we can look at the case studies that will be proposed throughout this book. To do this, we described KNIME software and KNIME Analytics Platform in detail.

KNIME Analytics Platform also benefits from an extension known as KNIME Deep Learning – Keras Integration, which helps with integrating Keras deep learning libraries...

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Codeless Deep Learning with KNIME

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

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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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