Text Mining in Data Science: An In-Depth Exploration Using NLTK

Text mining plays a crucial role in data science by transforming unstructured textual data into meaningful insights. This exploration delves into the methodologies and applications of text mining using the Natural Language Toolkit (NLTK), a powerful Python library for natural language processing. The talk will highlight key techniques such as tokenization, stemming, lemmatization, part-of-speech tagging, and sentiment analysis. By leveraging NLTK’s tools, data scientists can efficiently preprocess, analyze, and derive value from text data across various domains, making it an essential component in the broader landscape of data-driven decision-making. Speaker(s): , , Room: 4359, Bldg: ME, 1125 Colonel Dr, Ottawa, Ontario, Canada