- KNIME Tutorial
- KNIME - Home
- KNIME - Introduction
- KNIME - Installation
- KNIME - First Run
- KNIME - Workbench
- KNIME - Running Your First Workflow
- KNIME - Exploring Workflow
- KNIME - Building Your Own Model
- KNIME - Testing the Model
- KNIME - Summary and Future Work
- KNIME Useful Resources
- KNIME - Quick Guide
- KNIME - Useful Resources
- KNIME - Discussion
KNIME - Summary and Future Work
KNIME provides a graphical tool for building Machine Learning models. In this tutorial, you learned how to download and install KNIME on your machine.
You learned the various views provided in the KNIME workbench. KNIME provides several predefined workflows for your learning. We used one such workflow to learn the capabilities of KNIME. KNIME provides several pre-programmed nodes for reading data in various formats, analyzing data using several ML algorithms, and finally visualizing data in many different ways. Towards the end of the tutorial, you created your own model starting from scratch. We used the well-known iris dataset to classify the plants using k-Means algorithm.
You are now ready to use these techniques for your own analytics.
If you are a developer and would like to use the KNIME components in your programming applications, you will be glad to know that KNIME natively integrates with a wide range of programming languages such as Java, R, Python and many more.
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