Codeless Deep Learning with KNIME

5 (1 reviews total)
By Kathrin Melcher , Rosaria Silipo
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    Section 1: Feedforward Neural Networks and KNIME Deep Learning Extension
About this book

KNIME Analytics Platform is an open source software used to create and design data science workflows. This book is a comprehensive guide to the KNIME GUI and KNIME deep learning integration, helping you build neural network models without writing any code. It’ll guide you in building simple and complex neural networks through practical and creative solutions for solving real-world data problems.

Starting with an introduction to KNIME Analytics Platform, you’ll get an overview of simple feed-forward networks for solving simple classification problems on relatively small datasets. You’ll then move on to build, train, test, and deploy more complex networks, such as autoencoders, recurrent neural networks (RNNs), long short-term memory (LSTM), and convolutional neural networks (CNNs). In each chapter, depending on the network and use case, you’ll learn how to prepare data, encode incoming data, and apply best practices.

By the end of this book, you’ll have learned how to design a variety of different neural architectures and will be able to train, test, and deploy the final network.

Publication date:
November 2020


Section 1: Feedforward Neural Networks and KNIME Deep Learning Extension

This section is introductory. It is here to ease you into the world of neural networks and the tool at hand, KNIME Analytics Platform.

This section comprises the following chapters:

  • Chapter 1, Introduction to Deep Learning with KNIME Analytics Platform
  • Chapter 2, Data Access and Preprocessing with KNIME Analytics Platform
  • Chapter 3, Getting Started with Neural Networks
  • Chapter 4, Building and Training a Feedforward Neural Network
About the Authors
  • 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.

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  • Rosaria Silipo

    Rosaria Silipo has been working in data analytics since 1992. Currently, she is a principal data scientist at KNIME. In the past, she has held senior positions with Siemens, Viseca AG, and Nuance Communications, and worked as a consultant in a number of data science projects. She holds a Ph.D. in bioengineering from the Politecnico di Milano and a master’s degree in electrical engineering from the University of Florence (Italy). She is the author of more than 50 scientific publications, many scientific white papers, and a number of books for data science practitioners.

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Latest Reviews (1 reviews total)
Excelente libro. cumplio con mis expectativas
Codeless Deep Learning with KNIME
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