Tokens

In the context of natural language processing (NLP) and machine learning, tokens refer to the individual units of text that are processed by algorithms. These can be words, characters, or subwords, depending on the tokenization method used. Tokenization is a crucial step in preparing text data for analysis, as it breaks down sentences into manageable pieces. Common use cases include text classification, sentiment analysis, and language modeling, where understanding the structure and meaning of text is essential. The choice of tokenization strategy can significantly impact the performance of NLP models.