You're reading from Codeless Deep Learning with KNIME Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform

Product type Paperback

Published in Nov 2020

Publisher Packt

ISBN-13 9781800566613

Length 384 pages

Edition 1st Edition

Languages

Python

Tools

Knime

Concepts

Deep Learning

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 FREE CHAPTER

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

The Demand Prediction Problem

Let's continue then by exploring a demand prediction problem and how it can be treated as a time series analysis problem.

Demand prediction is a task related to the need to make estimates about the future. We all agree that knowing what lies ahead in the future makes life much easier. This is true for life events as well as, for example, the prices of washing machines and refrigerators, or demand for electrical energy in an entire city. Knowing how many bottles of olive oil customers will want tomorrow or next week allows for better restocking plans in retail stores. Knowing of a likely increase in the demand for gas or diesel allows a trucking company to better plan its finances. There are countless examples where this kind of knowledge of the future can be of help.

Demand Prediction

Demand prediction, or demand forecasting, is a big branch of data science. Its goal is to make estimations about future demand using historical data and possibly...