What are some of the prerequisites for clean data when it comes to machine learning, and how do you ensure they are all met?

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Anonymous · Accepted Answer

The data should be cleaned, pre processed and converted into the required format
necessary for the specific ML algorithm being used. For example, in case of
numeric or categorical data there could be missing values that should be
imputed. Values in certain columns may need to be bucketed. Unstructured data
has to be formatted in the required input format. In case of text data, we may
have to tokenize, lematize and perhaps also create an embedding of the text
data. The possibilities are many and depends on the specific task at hand.

What are some of the prerequisites for clean data when it comes to machine learning, and how do you ensure they are all met?

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