Codeless Deep Learning with KNIME: Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform

Melcher

KNIME AG

Rosaria Silipo

€41.99

4.5 (10 Ratings)

Paperback Nov 2020 384 pages 1st Edition

Melcher

KNIME AG

Rosaria Silipo

€41.99

4.5 (10 Ratings)

Paperback Nov 2020 384 pages 1st Edition

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Key benefits

Become well-versed with KNIME Analytics Platform to perform codeless deep learning
Design and build deep learning workflows quickly and more easily using the KNIME GUI
Discover different deployment options without using a single line of code with KNIME Analytics Platform

Description

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.

Who is this book for?

This book is for data analysts, data scientists, and deep learning developers who are not well-versed in Python but want to learn how to use KNIME GUI to build, train, test, and deploy neural networks with different architectures. The practical implementations shown in the book do not require coding or any knowledge of dedicated scripts, so you can easily implement your knowledge into practical applications. No prior experience of using KNIME is required to get started with this book.

What you will learn

Use various common nodes to transform your data into the right structure suitable for training a neural network
Understand neural network techniques such as loss functions, backpropagation, and hyperparameters
Prepare and encode data appropriately to feed it into the network
Build and train a classic feedforward network
Develop and optimize an autoencoder network for outlier detection
Implement deep learning networks such as CNNs, RNNs, and LSTM with the help of practical examples
Deploy a trained deep learning network on real-world data

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Economy: Delivery to most addresses in the U.K. within 7-9 business days.
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Amazon verified reviews

Bookworm Dec 07, 2020

Developing deep learning models is time demanding, and naturally difficult; the underlying techniques (architecture types) are fundamentally complex. It requires coding expertise. Well, at least that was the case, until now. This book makes things easy to understand and easy to implement, without coding.I liked the way the topics are laid out and sequenced: starting with the basics and foundations of KNIME, and then diving into Deep Learning with the extension, covering different DL architecture, and their codeless implementation in KNIME Analytics Platform.The coverage is comprehensive, motivational, conceptual, and with just about enough algorithmic/mathematical explanations and details.In summary, this book is one of a kind in that it explains highly technical, mostly code-based, deep learning algorithms in an easy to understand manner, using a visual modeling paradigm based on the KNIME Analytics Platform.

Amazon Verified review

Joe Porter Jan 24, 2021

KNIME continues to Impress! Since I first discovered KNIME 8-10 years ago I have been impressed by it’s ease of use and ability to quickly give analytically oriented people the ability to perform complex data engineering and data science tasks at scale.In this book, KNIME continues this tradition as it does a great job of teaching us multiple deep learning methods with real world use-cases.I would highly recommend this book and the KNIME software to anyone interested in Data Science but wants an alternative to code.

Dennis Ganzaroli Jun 24, 2021

Everything you need to know to get started quickly with Deep Learning

Vijaykrishna Venkataraman Dec 07, 2020

This book makes deep learning accessible to anyone with little or no prior programming experience. The user-friendly GUI integrations to the open-source KNIME Analytics Platform are built on robust and powerful deep learning frameworks like Keras and TensorFlow. Leverage on the shoulder of giants who already developed the tool and dive straight into trying your hands on some case studies without the burden/barrier of code. The authors provide the right mix of theoretical foundation followed by practical case studies on fraud detection, natural language processing (NLP), image classification, etc. The last section (two dedicated chapters) covers usually neglected topics, like implementing trained models to production and a much-needed chapter on deployment best practices. The deployment options include a web app or a REST web-service again without any coding in no time; however, it requires access to a licensed version of the KNIME Server.To summarize, if you learn best by doing, you can't go wrong with this book. I recommend this to someone who wants to get started but may feel a little lost and anxious. You'll want to check out the book's companion workflows at KNIME Hub. It contains lots of workflows with configured nodes and data that you can run right on your computer.

Stefano Jan 30, 2021

Very useful, it help for both to learn NN and to develop without codino! It's the base to democratize data

Codeless Deep Learning with KNIME: Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform

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