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You're reading from  Codeless Deep Learning with KNIME

Product typeBook
Published inNov 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781800566613
Edition1st Edition
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Authors (3):
Kathrin Melcher
Kathrin Melcher
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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

Rosaria Silipo
Rosaria Silipo
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Rosaria Silipo

Rosaria Silipo, Ph.D., now head of data science evangelism at KNIME, has spent 25+ years in applied AI, predictive analytics, and machine learning at Siemens, Viseca, Nuance Communications, and private consulting. Sharing her practical experience in a broad range of industries and deployments, including IoT, customer intelligence, financial services, social media, and cybersecurity, Rosaria has authored 50+ technical publications, including her recent books Guide to Intelligent Data Science (Springer) and Codeless Deep Learning with KNIME (Packt).
Read more about Rosaria Silipo

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Neural Networks and Deep Learning – Basic Concepts

All you hear about at the moment is deep learning. Deep learning stems from the traditional discipline of neural networks, in the realm of machine learning.

The field of neural networks has gone through a number of stop-and-go phases. Since the early excitement for the first perceptron in the '60s and the subsequent lull when it became evident what the perceptron could not do; through the renewed enthusiasm for the backpropagation algorithm applied to multilayer feedforward neural networks and the subsequent lull when it became apparent that training recurrent networks required hardware capabilities that were not available at the time; right up to today's new deep learning paradigms, units, and architectures running on much more powerful, possibly GPU-equipped, hardware.

Let's start from the beginning and, in this section, go through the basic concepts behind neural networks and deep learning. While these...

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Codeless Deep Learning with KNIME
Published in: Nov 2020Publisher: PacktISBN-13: 9781800566613

Authors (3)

author image
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

author image
Rosaria Silipo

Rosaria Silipo, Ph.D., now head of data science evangelism at KNIME, has spent 25+ years in applied AI, predictive analytics, and machine learning at Siemens, Viseca, Nuance Communications, and private consulting. Sharing her practical experience in a broad range of industries and deployments, including IoT, customer intelligence, financial services, social media, and cybersecurity, Rosaria has authored 50+ technical publications, including her recent books Guide to Intelligent Data Science (Springer) and Codeless Deep Learning with KNIME (Packt).
Read more about Rosaria Silipo