Codeless Time Series Analysis with KNIME: A practical guide to implementing forecasting models

[LeeAndro]

English | 2022 | ISBN: ‎ 1803232064 | 392 pages | True PDF EPUB | 46.35 MB

Perform series analysis using K Analytics Platform, covering both statistical methods and machine learning-based methods
Key Features

Gain a solid understanding of series analysis and its applications using K
Learn how to apply popular statistical and machine learning series analysis techniques
Integrate other tools such as Spark, H2O, and Keras with K 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 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 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 K Analytics Platform and other external tools.

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



DOWNLOAD

https://1dl.net/f5wxy3oimtpx/BOepC3R2_Codeless_Ti.rar.html