Theoretical aspects of Natural Language programming

In a recent blog post I discussed the theoretical aspects of time series analysis, which can be found here:- https://tracyrenee61.medium.com/musings-of-a-time-series-analyst-forecaster-3146c2ed41cd

I thought that since I have undertaken a bit of work making predictions on text data, perhaps it would be a good idea to make a blog post on natural language processing (NLP) as well:-

Text mining

Text mining is the process of exploring and analysing a large collection of unstructured textual data and deriving useful information, patterns, and actionable insights from it.

Why do we need to mine text?

1. There is an unprecedented amount of structured text data being generated every day.
2. Text mining transforms unstructured data into structured data to further be used for analysis.
3. To identify business insights to fuel business processes and reduce risks to the business.
4. To make informed decisions, automate processes, conduct market research research using sentiment analysis, etcetera.

Areas of text mining

1. Information extraction,
2. Document classification and clustering, and