All Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Codeless Deep Learning with KNIME

You're reading from Codeless Deep Learning with KNIME

Product type Book

Published in Nov 2020

Publisher Packt

ISBN-13 9781800566613

Pages 384 pages

Edition 1st Edition

Languages

Concepts

Authors (3):

Kathrin Melcher

KNIME AG

Rosaria Silipo

View More author details

Table of Contents (16) Chapters

Preface

1. Section 1: Feedforward Neural Networks and KNIME Deep Learning Extension

2. Chapter 1: Introduction to Deep Learning with KNIME Analytics Platform

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

Leave a review - let other readers know what you think

Optimizing the Autoencoder Strategy

What is the best value to use for threshold ? In the last section, we adopted based on our experience. However, is this the best value for ? Threshold , in this case, is not automatically optimized via the training procedure. It is just a static parameter external to the training algorithm. In KNIME Analytics Platform, it is also possible to optimize static parameters outside of the Learner nodes.

Optimizing Threshold

Threshold is defined on a separate subset of data, called the optimization set. There are two options here:

If an optimization set with labeled fraudulent transactions is available, the value of threshold is optimized against any accuracy measure for fraud detection.
If no labeled fraudulent transactions are available in the dataset, the value of threshold is defined as a high percentile of the reconstruction errors on the optimization set.

During the data preparation phase, we generated three data subsets...

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $15.99/month. Cancel anytime}

Authors (3)

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.

See other products by Kathrin Melcher

KNIME AG

See other products by KNIME AG

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

See other products by Rosaria Silipo

Other recommended products

Related to this chapter

Data Analytics Made Easy

Data Analytics Made Easy

This book takes away the fear of working with, analyzing, and visualizing data. Understand the key concepts involved with data analytics while working with real-world business examples. You are introduced to two fantastic tools to cleanse and analyze data (KNIME) and visualize your insights (Microsoft Power BI), but the principles from this book can apply to any platform you decide to use.

Aug 2021 13 hours 32 minutes

Intelligent Projects Using Python

Intelligent Projects Using Python

This book includes 9 projects on building smart and practical AI-based systems. These projects cover solutions to different domain-specific problems in healthcare, e-commerce and more. With this book, you will apply different machine learning and deep learning techniques and learn how to build your own intelligent applications for smart predictions and other insight-driven tasks.

Jan 2019 11 hours 24 minutes

Hands-On Natural Language Processing with PyTorch 1.x

Hands-On Natural Language Processing with PyTorch 1.x

Developers working with NLP will be able to put their knowledge to work with this practical guide to PyTorch. You will learn to use PyTorch offerings and how to understand and analyze text using Python. You will learn to extract the underlying meaning in the text using deep neural networks and modern deep learning algorithms.

Jul 2020 9 hours 12 minutes

Hands-On Java Deep Learning for Computer Vision

Hands-On Java Deep Learning for Computer Vision

This book will take you through the process of efficiently training deep neural networks in Java for Computer Vision-related tasks. You will build real-world applications ranging from simple Java handwritten digit recognition models to real-time autonomous car driving systems and face recognition models using the popular Java-based libraries.

Feb 2019 8 hours 40 minutes

Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing

Starting with the basics, this book teaches you how to choose from the various text pre-processing techniques and select the best model from the several neural network architectures for NLP issues.

Jun 2019 12 hours 24 minutes

Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

Cognitive Toolkit is one of the most popular and recently open sourced deep learning toolkit by Microsoft. Cognitive Toolkit is used to train fast and effective deep learning models. This book will be a quick introduction to using Cognitive Toolkit and will teach you how to train and validate different types of neural networks.

Mar 2019 6 hours 56 minutes

Neural Network Projects with Python

Neural Network Projects with Python

This book contains practical implementations of several deep learning projects in multiple domains, including in regression-based tasks such as taxi fare prediction in New York City, image classification of cats and dogs using a convolutional neural network, implementing a facial recognition security system using Siamese Neural Networks, and more.

Feb 2019 10 hours 16 minutes

Natural Language Processing with TensorFlow

Natural Language Processing with TensorFlow

TensorFlow is the leading framework for deep learning algorithms critical to artificial intelligence, and natural language processing (NLP) makes much of the data used by deep learning applications accessible to them. This book brings the two together and teaches deep learning developers how to work with today’s vast amount of unstructured data.

May 2018 15 hours 44 minutes

Deep Learning Quick Reference

Deep Learning Quick Reference

This book is a practical guide to applying deep neural networks including MLPs, CNNs, LSTMs, and more in Keras and TensorFlow. Packed with useful hacks to solve real-world challenges along with the supported math and theory around each topic, this book will be a quick reference for training and optimize your deep neural networks.

Mar 2018 9 hours 4 minutes

Hands-On Neural Networks

Hands-On Neural Networks

This book will be a journey for beginners who want to step into the world of deep learning and artificial intelligence. It will thoughtfully take you through the training and implementation of various neural network architectures using the Python ecosystem. You will master each neural network architecture while understanding its working mechanism.

May 2019 9 hours 20 minutes

Hands-On Python Natural Language Processing

Hands-On Python Natural Language Processing

This book provides a blend of both the theoretical and practical aspects of Natural Language Processing (NLP). It covers the concepts essential to develop a thorough understanding of NLP and also delves into a detailed discussion on NLP based use-cases such as language translation, sentiment analysis, etc. Every module covers real-world examples

Jun 2020 10 hours 32 minutes

Hands-On Deep Learning Architectures with Python

Hands-On Deep Learning Architectures with Python

This book explains the essential learning algorithms used for deep and shallow architectures. Packed with practical implementations to help you understand the concepts and ideas required to build efficient artificial intelligence systems, this book will help you construct deep models using popular frameworks and datasets.

Apr 2019 10 hours 32 minutes

Personalised recommendations for you

Based on your interests and search pattern

Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.

Aug 2023 7 hours 40 minutes

Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Dec 2023 12 hours 0 minutes

Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Dec 2023 12 hours 0 minutes

Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Dec 2023 12 hours 0 minutes

Generative AI with LangChain

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Dec 2023 12 hours 0 minutes

Mastering Tableau 2023

Mastering Tableau 2023

This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.

Aug 2023 22 hours 48 minutes

Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

Sep 2023 8 hours 36 minutes

Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

Sep 2023 8 hours 36 minutes

Data Engineering with AWS

Data Engineering with AWS

Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.

Oct 2023 21 hours 12 minutes

Modern Data Architecture on AWS

Modern Data Architecture on AWS

Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.

Aug 2023 14 hours 0 minutes

Practical Guide to Applied Conformal Prediction in Python

Practical Guide to Applied Conformal Prediction in Python

Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.

Dec 2023 8 hours 0 minutes

TinyML Cookbook

TinyML Cookbook

With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.

Nov 2023 22 hours 8 minutes