July 2017
Beginner to intermediate
486 pages
13h 49m
English
Content preview from Python Natural Language Processing
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Cleaning
In this step, we clean the data. If the dataset has missing values, either delete that data record or replace it with the most appropriate nearest value. If you find any unnecessary data attributes, you can remove them as well. Suppose you are making a grammar correction system, then you can remove the mathematical equations from your dataset because your grammar correction application doesn't use equations.
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