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To maximize prediction accuracy, human participation is crucial during data preparation. #
The first step in any ML activity starts with data. Data must be clean and properly preprocessed before working with it. Based on the type of learning, one can preprocess data. A human exploration is needed to understand the type and quality of the data and the relationships among data elements/attributes.
The following are typical Preparation activities performed once input data enters the ML system.
- Understand the type of data given in the input data set
- Explore the data to understand nature & quality.
- Explore the relationships among the data elements, e.g., inter-feature relationships.
- Find potential issues in the data
- Do the necessary remediation, e.g., impute missing values if needed.
- Apply pre-processing steps, as necessary.
Here, we will learn each activity in detail.
Once data is prepared for modelling, the learning tasks start off…
source & further reading
pub.towardsai.net — original article
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