In NLP, researchers and computer scientists try to make a computer understand an English (or any other human language) sentence. The result of their hard work can be seen in many modern applications, such as the voice assistants Apple Siri or Amazon Alexa.
But before going into such advanced systems, NLP can be used to do the following:
- Perform sentiment analysis: Is a comment about a specific brand positive or negative?
- Named Entity Recognition (NER): Can we extract the name of people or locations contained within a given text, without having to list them all in a regex pattern?
These two questions, quite easy for a human being, are incredibly hard for a machine. The models used to achieve very good results are beyond the scope of this book, but you can refer to the Further reading section to learn more about them.
In the next section, we are going to use pre-trained models provided by the NLP research group from Stanford University, which provides state-of-the-art results...
