Summary

In this chapter, we studied NLP, which automatically processes information that’s transmitted through spoken or written language. To begin, we analyzed the basic concepts of NLP by identifying the tasks that can be tackled and then moved on to the main approaches concerning text analysis and text generation. We then moved on to analyze corpora, words, and sentence tokenization. Corpora offers authentic language data for examination, with words serving as the fundamental components of expression, and sentence tokenization organizing the text into coherent units for in-depth analysis.

In the second part of this chapter, we analyzed a practical case of using NLP for labeling movie reviews. This is a sentiment analysis problem that aims to automatically identify the polarity of a textual comment. In this example, we were able to practically learn which tools to use in MATLAB to perform this type of analysis. In the final part of this chapter, we analyzed ensemble learning...