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Codeless Time Series Analysis with KNIME

You're reading from   Codeless Time Series Analysis with KNIME A practical guide to implementing forecasting models for time series analysis applications

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781803232065
Length 392 pages
Edition 1st Edition
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Authors (4):
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Daniele Tonini Daniele Tonini
Author Profile Icon Daniele Tonini
Daniele Tonini
Maarit Widmann Maarit Widmann
Author Profile Icon Maarit Widmann
Maarit Widmann
Corey Weisinger Corey Weisinger
Author Profile Icon Corey Weisinger
Corey Weisinger
KNIME AG KNIME AG
Author Profile Icon KNIME AG
KNIME AG
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Toc

Table of Contents (20) Chapters Close

Preface 1. Part 1: Time Series Basics and KNIME Analytics Platform
2. Chapter 1: Introducing Time Series Analysis FREE CHAPTER 3. Chapter 2: Introduction to KNIME Analytics Platform 4. Chapter 3: Preparing Data for Time Series Analysis 5. Chapter 4: Time Series Visualization 6. Chapter 5: Time Series Components and Statistical Properties 7. Part 2: Building and Deploying a Forecasting Model
8. Chapter 6: Humidity Forecasting with Classical Methods 9. Chapter 7: Forecasting the Temperature with ARIMA and SARIMA Models 10. Chapter 8: Audio Signal Classification with an FFT and a Gradient-Boosted Forest 11. Chapter 9: Training and Deploying a Neural Network to Predict Glucose Levels 12. Chapter 10: Predicting Energy Demand with an LSTM Model 13. Chapter 11: Anomaly Detection – Predicting Failure with No Failure Examples 14. Part 3: Forecasting on Mixed Platforms
15. Chapter 12: Predicting Taxi Demand on the Spark Platform 16. Chapter 13: GPU Accelerated Model for Multivariate Forecasting 17. Chapter 14: Combining KNIME and H2O to Predict Stock Prices 18. Answers 19. Other Books You May Enjoy

Technical requirements

The following are the prerequisites for this chapter.

  • KNIME Analytics Platform with KNIME Extension for Apache Spark to be installed
  • For local execution: KNIME Extension for Local Big Data Environments to be installed
  • For remote execution: The KNIME Big Data Connectors extension, or a dedicated extension for connecting to cloud storage to be installed

All the workflows introduced in the chapter are available on the KNIME Hub under https://kni.me/s/XfLEQY_FHw3-CI1P and on GitHub under https://github.com/PacktPublishing/Codeless-Time-Series-Analysis-with-KNIME/tree/main/Chapter12. The optional workflows for accessing and preprocessing big data are available on the KNIME Hub under https://kni.me/w/yZI74OtdOBVajpsT.

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