Natural Language Processing (NLP)

Natural Language Processing (NLP) is a field of AI that focuses on the interaction between computers and human language. The challenge in NLP is for computers to understand, interpret, and generate human language in a way that is both meaningful and useful.

In this chapter, we’ll explore key NLP tasks such as tokenization, the process of breaking text into smaller units like words or phrases. We’ll also discuss sentiment analysis, which involves determining whether the sentiment expressed in a text is positive, negative, or neutral. Named entity recognition is another NLP task that helps identify specific items like people, places, and dates within a body of text.

You’ll also learn about powerful NLP models like BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pretrained Transformer). These models have revolutionized the way machines understand and generate human language, enabling applications like chatbots, translation, and text summarization.

By the end of this chapter, you will have gained an understanding of how computers process language, opening the door for creating intelligent applications that can interact with users in natural ways.