To load some data, click the green button. Since this article deals with building and implementing a machine learning model I will select the Turbo Prep option. After creating your account you will see this screen in front of you.ĭepending on your requirements you can select whichever template you would like to use.Once done, wait for the download to complete and set up your account in the studio. Download the ‘Rapid Miner Studio’ option and select the operating system type of your system. The first step is to download the rapid miner tool in your local system.A Step-by-Step Guide to Using Rapid Miner You just need to create user interfaces to collect real-time data and run it on the trained model to serve a task.īecause of all of the above-mentioned facilities, users find this tool very useful and easy to use when compared to platforms like Tensorflow or Keras. Finally, to bind everything together, you can easily deploy your machine learning models to the web or to mobiles through this platform.Not only this, but the tool also provides the ability to perform pruning and tuning. You can also train optimal deep learning algorithms like Gradient Boost, XGBoost etc. Rapid Miner provides a wide range of machine learning algorithms in classification, clustering and regression as well.The standard implementation of procedures like data cleaning, visualization, pre-processing can be done with drag and drop options without having to write even a single line of code.Apart from this, you can load your CSV data very easily and start using it as well. You can store and load the data from Hadoop, Cloud, RDBMS, NoSQL etc. 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.
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