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If it works, keep it simple
As we all know, a big part of a data scientist’s job is to clean and preprocess data. A huge part of this involves outlier detection and removal. Large outliers, spikes and bad data can really interfere with training an accurate machine learning model, so it’s important that outliers are handled properly.
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