Introduction Natural Language Processing (NLP) is a cornerstone of modern artificial intelligence, enabling machines to understand, interpret, and generate human language in a way that is natural and useful. Over the years, various models have been developed to improve the way machines handle language. Among these, Bidirectional Encoder Representations from Transformers (BERT) stands out as … Read more
In the rapidly evolving world of artificial intelligence, prompting has emerged as a crucial technique for interacting with generative AI models. It acts as the bridge between human intention and machine output, shaping the quality and relevance of the AI’s responses.
The primary goals of EDA in NLP include understanding data distribution, identifying patterns, detecting outliers, and uncovering relationships among variables. These insights allow data scientists to formulate hypotheses, guide data collection, and inform model selection and tuning.