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Codeless Deep Learning with KNIME

You're reading from   Codeless Deep Learning with KNIME Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781800566613
Length 384 pages
Edition 1st Edition
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Authors (3):
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Kathrin Melcher Kathrin Melcher
Author Profile Icon Kathrin Melcher
Kathrin Melcher
KNIME AG KNIME AG
Author Profile Icon KNIME AG
KNIME AG
Rosaria Silipo Rosaria Silipo
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Rosaria Silipo
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Feedforward Neural Networks and KNIME Deep Learning Extension
2. Chapter 1: Introduction to Deep Learning with KNIME Analytics Platform FREE CHAPTER 3. Chapter 2: Data Access and Preprocessing with KNIME Analytics Platform 4. Chapter 3: Getting Started with Neural Networks 5. Chapter 4: Building and Training a Feedforward Neural Network 6. Section 2: Deep Learning Networks
7. Chapter 5: Autoencoder for Fraud Detection 8. Chapter 6: Recurrent Neural Networks for Demand Prediction 9. Chapter 7: Implementing NLP Applications 10. Chapter 8: Neural Machine Translation 11. Chapter 9: Convolutional Neural Networks for Image Classification 12. Section 3: Deployment and Productionizing
13. Chapter 10: Deploying a Deep Learning Network 14. Chapter 11: Best Practices and Other Deployment Options 15. Other Books You May Enjoy

The Importance of Deep Learning

If you have been working in the field of data science – or Artificial Intelligence (AI), as it is called nowadays – for a few years, you might have noticed the recent sudden explosion of scholarly and practitioner articles about successful solutions based on deep learning techniques.

The big breakthrough happened in 2012 when the deep learning-based AlexNet network won the ImageNet challenge by an unprecedented margin. This victory kicked off a surge in the usage of deep learning networks. Since then, these have expanded to many different domains and tasks.

So, what are we referring to exactly when we talk about deep learning? Deep learning covers a subset of Machine Learning (ML) algorithms, most of which stem from neural networks. Deep learning is indeed the modern evolution of traditional neural networks. Apart from the classic feedforward, fully connected, backpropagation-trained, and multilayer perceptron architectures, deeper...

You have been reading a chapter from
Codeless Deep Learning with KNIME
Published in: Nov 2020
Publisher: Packt
ISBN-13: 9781800566613
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