Tag: KNIME

December 29, 2023

Predictive Analytics with KNIME Analytics for Citizen Data Scientists

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Free Download Predictive Analytics with KNIME: Analytics for Citizen Data Scientists
English | 2023 | ISBN: 3031456297 | 327 Pages | PDF EPUB (True) | 42 MB
This book is about data analytics, including problem definition, data preparation, and data analysis. A variety of techniques (e.g., regression, logistic regression, cluster analysis, neural nets, decision trees, and others) are covered with conceptual background as well as demonstrations of KNIME using each tool.

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December 25, 2023

Codeless Time Series Analysis with KNIME

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Free Download Codeless Time Series Analysis with KNIME: A practical guide to implementing forecasting models for time series analysis applications by Corey Weisinger, Maarit Widmann, Daniele Tonini
English | August 19, 2022 | ISBN: 1803232064 | 392 pages | MOBI | 27 Mb
Perform time series analysis using KNIME Analytics Platform, covering both statistical methods and machine learning-based methods

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July 22, 2023

Introduction to Machine Learning with KNIME

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Free Download Introduction to Machine Learning with KNIME
Updated: 07/2023
Duration: 1h 59m | .MP4 1280×720, 30 fps(r) | AAC, 48000 Hz, 2ch | 329 MB
Level: Beginner + Intermediate | Genre: eLearning | Language: English
KNIME is an open-source workbench-style tool for predictive analytics and machine learning. It is highly compatible with numerous data science technologies, including R, Python, Scala, and Spark. With KNIME, you can produce solutions that are virtually self-documenting and ready for use. These reasons and more make KNIME one of the most popular and fastest-growing analytics platforms around. In this course, expert Keith McCormick shows how KNIME supports all the phases of the Cross Industry Standard Process for Data Mining (CRISP-DM) in one platform. Get up and running quickly-in 15 minutes or less-or stick around for the more in-depth training covering merging and aggregation, modeling, and data scoring. Plus, learn how to increase the power of KNIME with extensions and integrate R and Python.

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