Codeless Deep Learning with KNIME

The book begins with an easy introduction to KNIME Analytics Platform, covering traditional feed-forward neural networks, and then shows you how to use a backpropagation algorithm with the help of practical examples. You’ll also learn how to build simple and more complex neural networks within KNIME Analytics Platform, without using a single line of code. You will start with a simple feed-forward network to solve a simple classification problem on a small dataset. Having covered the basic concepts, you’ll move on to prepare data accordingly; apply best practices to avoid overfitting; and 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 the concluding chapters, you’ll explore practical and creative solutions for solving real-world data problems.

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

A free copy of chapter one is available here for download.