So far, we have reviewed the main concepts and areas surrounding natural language processing (NLP) and text analytics. We also got a good grip on the Python programming language in the last chapter, especially on the different constructs and syntax and how to work with strings to manage textual data. To carry out different operations and analyze text, you will need to process and parse textual data into more easy-to-interpret formats.
All machine learning (ML) algorithms , be they supervised or unsupervised techniques, usually work with input features that are numeric in ...
