Codeless Time Series Analysis with KNIME [ebook]
Codeless Time Series Analysis with KNIME
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.
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Author Details

<a href="https://market.tutorialspoint.com/author/daniele_tonini">Daniele Tonini</a>
Packt are an established, trusted, and innovative global technical learning publisher, founded in Birmingham, UK with over eighteen years experience delivering rich premium content from ground-breaking authors and lecturers on a wide range of emerging and established technologies for professional development.
Packt’s purpose is to help technology professionals advance their knowledge and support the growth of new technologies by publishing vital user focused knowledge-based content faster than any other tech publisher, with a growing library of over 9,000 titles, in book, e-book, audio and video learning formats, our multimedia content is valued as a vital learning tool and offers exceptional support for the development of technology knowledge.
We publish on topics that are at the very cutting edge of technology, helping IT professionals learn about the newest tools and frameworks in a way that suits them.
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