Download Predictive Analytics with KNIME 2025 (Russian Edition)
Predictive Analytics with KNIME 2025 is a practical guide to machine learning and data analysis using the KNIME platform. The book introduces readers to modern analytical workflows and demonstrates how machine learning techniques can be applied through KNIME’s intuitive visual environment.
KNIME is an open-source data science platform that enables users to design, execute, and analyze workflows through a graphical interface. Its drag-and-drop approach allows complex analytical processes to be created and monitored step by step, making data analysis more transparent and easier to reproduce. Support for Python and R scripts further extends KNIME’s capabilities and makes it a flexible tool for advanced data analysis.
The book covers essential machine learning methods, including linear and logistic regression, clustering techniques, decision trees, neural networks, and other commonly used algorithms. Along with theoretical concepts, it explains how these methods can be implemented in real-world projects using KNIME workflows.
Main topics covered in the book:
- Introduction to the KNIME analytics platform;
- Defining analytical problems and preparing data for analysis;
- Feature engineering and dimensionality reduction techniques;
- Practical implementation of machine learning algorithms with KNIME.
This book is suitable for data analysts, researchers, students, and anyone interested in learning the fundamentals of machine learning and data mining through a free, powerful, and user-friendly visual analytics tool.
- Author (s): Ginko Aleksandr Yurievich
- Year of publication: 2025
- Publisher: Springer
- Language: Russian
- ISBN: 9785937003546
- Number of pages: 362 pages
- Book format: PDF
- File size: 11 MB
