- KNIME - Discussion
- KNIME - Useful Resources
- KNIME - Quick Guide
- KNIME - Summary and Future Work
- KNIME - Testing the Model
- KNIME - Building Your Own Model
- KNIME - Exploring Workflow
- KNIME - Running Your First Workflow
- KNIME - Workbench
- KNIME - First Run
- KNIME - Installation
- KNIME - Introduction
- KNIME - Home
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
KNIME - Introduction
Developing Machine Learning models is always considered very challenging due to its cryptic nature. Generally, to develop machine learning apppcations, you must be a good developer with an expertise in command-driven development. The introduction of KNIME has brought the development of Machine Learning models in the purview of a common man.
KNIME provides a graphical interface (a user friendly GUI) for the entire development. In KNIME, you simply have to define the workflow between the various predefined nodes provided in its repository. KNIME provides several predefined components called nodes for various tasks such as reading data, applying various ML algorithms, and visuapzing data in various formats. Thus, for working with KNIME, no programming knowledge is required. Isn’t this exciting?
The upcoming chapters of this tutorial will teach you how to master the data analytics using several well-tested ML algorithms.
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