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Making sense of raw text is a hot topic, whether it is understanding financial https://www.veryfi.com/, finding https://www.bearer.com/, or improving that important email you http://grammarly.com/. Classifying text is a task that can be solved by utilizing Machine Learning (ML) and, more specifically https://thenewstack.io/machine-learning-still-struggles-to-extract-meaning-from-language/ (NLP) tools, or by using a more deterministic approach with pattern matching, also known as regular expressions. Both approaches have their own strengths and weaknesses, and in many cases, it may be beneficial to use a combination of both methods.
The advantage of using an ML model is that it can produce accurate text classification on any newly introduced data.
Train your NLP model using the training set and evaluate the model’s performance with the testing set.