Codeless Time Series Analysis with KNIME

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Codeless Time Series Analysis with KNIME

Codeless Time Series Analysis with KNIME


This eBook includes

Formats : PDF (Read Only)

Pages : 392

ISBN : 9781803239972

Language : English

About the Book

Book description

Perform time series analysis using KNIME Analytics Platform, covering both statistical methods and machine learning-based methods

Key Features

  • Gain a solid understanding of time series analysis and its applications using KNIME
  • Learn how to apply popular statistical and machine learning time series analysis techniques
  • Integrate other tools such as Spark, H2O, and Keras with KNIME within the same application

Book Description

This book will take you on a practical journey, teaching you how to implement solutions for many use cases involving time series analysis techniques.

This learning journey is organized in a crescendo of difficulty, starting from the easiest yet effective techniques applied to weather forecasting, then introducing ARIMA and its variations, moving on to machine learning for audio signal classification, training deep learning architectures to predict glucose levels and electrical energy demand, and ending with an approach to anomaly detection in IoT. There’s no time series analysis book without a solution for stock price predictions and you’ll find this use case at the end of the book, together with a few more demand prediction use cases that rely on the integration of KNIME Analytics Platform and other external tools.

By the end of this time series book, you’ll have learned about popular time series analysis techniques and algorithms, KNIME Analytics Platform, its time series extension, and how to apply both to common use cases.

What you will learn

  • Install and configure KNIME time series integration
  • Implement common preprocessing techniques before analyzing data
  • Visualize and display time series data in the form of plots and graphs
  • Separate time series data into trends, seasonality, and residuals
  • Train and deploy FFNN and LSTM to perform predictive analysis
  • Use multivariate analysis by enabling GPU training for neural networks
  • Train and deploy an ML-based forecasting model using Spark and H2O

Who this book is for

This book is for data analysts and data scientists who want to develop forecasting applications on time series data. While no coding skills are required thanks to the codeless implementation of the examples, basic knowledge of KNIME Analytics Platform is assumed. The first part of the book targets beginners in time series analysis, and the subsequent parts of the book challenge both beginners as well as advanced users by introducing real-world time series applications.

Codeless Time Series Analysis with KNIME

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Author Details

Packt Publishing

Packt Publishing

Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals.

Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools.

As part of our mission, we have also awarded over $1,000,000 through our Open Source Project Royalty scheme, helping numerous projects become household names along the way.

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