There are a plethora of visualization types available as shown below.
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Here you can play around with data visualization and see how to points are related to each other. To the left click on the visualization button. For visualization purposes of the data, you can click on the result button, drag and drop your dataset and you will be able to see few options as shown below.You can also load your own dataset either from your local system or from a database by clicking on the Import data option. Once you have navigated to this folder you can see a list of datasets. 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.
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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.
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