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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
Author Profile Icon Rosaria Silipo
Rosaria Silipo
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Toc

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

Chapter 1: Introduction to Deep Learning with KNIME Analytics Platform

We'll start our journey of exploring Deep Learning (DL) paradigms by looking at KNIME Analytics Platform. If you have always been drawn to neural networks and deep learning architectures and have always thought that the coding part would be an obstacle to you developing a quick learning curve, then this is the book for you.

Deep learning can be quite complex, and we must make sure that the journey is worth the result. Thus, we'll start this chapter by stating, once again, the relevance of deep learning techniques when it comes to successfully implementing applications for data science.

We will continue by providing a quick overview of the tool of choice for this book – KNIME Software – and focus on how it complements both KNIME Analytics Platform and KNIME Server.

The work we'll be doing throughout this book will be implemented in KNIME Analytics Platform, which is open source...

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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