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Real-world data is dirty. In order to get it ready for modeling, you need to deal with missing values, correct erroneous values, select relevant attributes and adapt dataset format to the model type – which consumes a lot of your valuable time!

Luckily, the hundreds of blending, cleansing, filtering, feature generation and munging functions in RapidMiner Studio, allow you to expertly format your data for predictive modeling – in a very fast and efficient way.

Watch this webinar to learn how to dramatically reduce the time spent on basic and advanced data prep tasks such as Data Exploration, Replacing/Imputing Missing Values, Replacing Nominal/String Values, Feature Generation, Handling Outliers, and more!

Download the sample data set used in this webinar.