Natural language understanding

NLU enables the processing of unstructured text and extracts meaning and critical pieces of information that are actionable. Enabling a computer to understand sentences of text is a very hard challenge. One aspect of NLU is understanding the meaning of sentences. Sentiment analysis of a sentence becomes possible after understanding the sentence. Another useful application is the classification of sentences to a topic. This topic classification can also help in the disambiguation of entities. Consider the following sentence: "A CNN helps improve the accuracy of object recognition." Without understanding that this sentence is about machine learning, an incorrect inference may be made about the entity CNN. It may be interpreted as the news organization as opposed to a deep learning architecture used in computer vision. An example of a sentiment analysis model is built using a specific RNN architecture called BiLSTMs later in this chapter.

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