/strings-regular-expressions-and-text-data-analysis

While built-in string methods and regular expressions have limitations, they can be leveraged in creative ways to implement scalable workflows that process and analyze text data. This article explores these tools and introduces a few useful peripheral techniques within the context of a use case involving a large text data corpus.

Primary LanguageJupyter NotebookMIT LicenseMIT

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