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Codeless Time Series Analysis with KNIME
Codeless Time Series Analysis with KNIME

Codeless Time Series Analysis with KNIME: A practical guide to implementing forecasting models for time series analysis applications

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Profile Icon KNIME AG Profile Icon Corey Weisinger Profile Icon Maarit Widmann Profile Icon Daniele Tonini
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£9.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (10 Ratings)
Paperback Aug 2022 392 pages 1st Edition
eBook
£28.99
Paperback
£35.99
Subscription
Free Trial
Renews at £9.99p/m
Arrow left icon
Profile Icon KNIME AG Profile Icon Corey Weisinger Profile Icon Maarit Widmann Profile Icon Daniele Tonini
Arrow right icon
£9.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.8 (10 Ratings)
Paperback Aug 2022 392 pages 1st Edition
eBook
£28.99
Paperback
£35.99
Subscription
Free Trial
Renews at £9.99p/m
eBook
£28.99
Paperback
£35.99
Subscription
Free Trial
Renews at £9.99p/m

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Key benefits

  • 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

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.

Who is this book 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.

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 19, 2022
Length: 392 pages
Edition : 1st
Language : English
ISBN-13 : 9781803232065
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Product Details

Publication date : Aug 19, 2022
Length: 392 pages
Edition : 1st
Language : English
ISBN-13 : 9781803232065
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Total £ 117.97
Modern Time Series Forecasting with Python
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Total £ 117.97 Stars icon
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Customer reviews

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Full star icon Full star icon Full star icon Full star icon Half star icon 4.8
(10 Ratings)
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buyer Mar 15, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very good book
Amazon Verified review Amazon
Amazon Customer Aug 19, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is book is pretty good not only for those who are interested in doing time series analysis in KNIME, but also good to understand key time series concepts in general. Many chapters of the book introduce concepts (and how to execute them in KNIME) in the context of an application, which really facilitates learning. I especially like Chapter 7, which introduces (S)ARIMA models in the context of temperature forecasting.
Amazon Verified review Amazon
Abdul Aug 19, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book makes it easy to digest different types of Time Series without having to worry about having to learn how to code. It breaks down the different types of Time Series that you can run across with real life business use cases and some education ones as well. The books is fairly practical and if you want to deep-dive into the math or theory a bit more it opens the door for you there.
Amazon Verified review Amazon
John Emery Aug 29, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Disclosure: I was given an advance copy of this book and asked to provide a balanced review.I found this book to be a thorough, but not overly technical, examination of time series analytic techniques and their application in KNIME Analytics Platform. Very little background with time series analysis or higher mathematics is assumed. However, that experience certainly wouldn't hurt, as some topics can be challenging—Fourier transforms and neural networks, to name just two.One of my favorite aspects of the book is that it clearly describes how to perform these analytic techniques within KNIME. The exact nodes and configurations are shown, and explanations are given on why nodes are configured the way they are. The reader is not left wondering, "why did they do this step?" Ignoring the topic of time series analysis, the reader of this book will, at the very least, come away with a better understanding of KNIME Analytics Platform and its many available nodes.In my day job, I work with clients who use KNIME. I will use this book as a resource and guide when I need examples for time series analysis questions. I absolutely recommend this book to any KNIME user interested in these topics.
Amazon Verified review Amazon
Jeff Gullick Sep 21, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
My background is more in data integration and business intelligent, and less with data science.This is a fantastic book if you are like me and don't have a DS background. I very much appreciated the time taken to point out and walk through data preparation for time series analysis (TSA).The sections discuss different deployment methods and technologies was a highlight for me. Showing how the same model/process can be deployed via different technologies like Spark and H2O gives the readers ideas on different deployment options depending on their requirements.There is a lot of information and having experience with data wrangling or data science does make absorbing and understanding the material easier.
Amazon Verified review Amazon
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