Book Image

Codeless Deep Learning with KNIME

By : Kathrin Melcher, KNIME AG, Rosaria Silipo
Book Image

Codeless Deep Learning with KNIME

By: Kathrin Melcher, KNIME AG, Rosaria Silipo

Overview of 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.
Table of Contents (16 chapters)
1
Section 1: Feedforward Neural Networks and KNIME Deep Learning Extension
6
Section 2: Deep Learning Networks
12
Section 3: Deployment and Productionizing

Why is Detecting Fraud so Hard?

Fraud detection is a set of activities undertaken to prevent money or property from being obtained through false pretenses. Fraud detection is applied in many industries, such as banking or insurance. In banking, fraud may include forging checks or using stolen credit cards. For this example, we will focus on fraud in credit card transactions.

This kind of fraud, in credit card transactions, is a huge problem for credit card issuers as well as for the final payers. The European Central Bank reported that in 2016, the total number of card fraud cases using cards issued in the Single Euro Payments Area (SEPA) amounted to 17.3 million, and the total number of card transactions using cards issued in SEPA amounted to 74.9 billion (https://www.ecb.europa.eu/pub/cardfraud/html/ecb.cardfraudreport201809.en.html#toc1).

However, the amount of fraud is not the only problem. From a data science perspective, fraud detection is also a very hard task to solve...