Rapid Miner is a platform for data scientists and big data analysts to quickly analyse their data. Rapid Miner has taken a huge leap in the AI community since it is most popularly used by non-programmers and researchers. The platform provides a vast number of options in terms of plugins and data analysis techniques. Apart from this, it is also compatible with iOs, Android, and web application tools like Node JS and flask. This platform is useful for anyone with an idea they would like to experiment with without spending much time or effort on it.
In this article, we will learn about the architecture of Rapid Miner tool and learn the step by step approach to using the tool to build a machine learning model.
The Architecture of RapidMiner
The idea behind Rapid Mining tool is to create one place for everything. Starting from providing multiple datasets to model deployment through the platform you can do it all here. Some of the facilities of this platform are:
- Rapid Miner provides its own collection of datasets but it also provides options to set up a database in the cloud for storing large amounts of data. You can store and load the data from Hadoop, Cloud, RDBMS, NoSQL etc. Apart from this, you can load your CSV data very easily and start using it as well.
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