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Imagine you work for a company that publishes scientific articles created by its customers—primarily researchers and scientists in the field of statistics—whose volume of research has grown so large that it’s not possible for your company to read every paper nor for the researchers to stay on top of everything happening in the field. Your task is to use automated means to find some structure in the collection of scientific articles so that the company can more easily home in on the researchers’ interests and help them research more effectively. To do that, you’ll generate document embeddings, use them to impute a document graph, and execute graph algorithms against this graph in order to generate insights from it.
This liveProject is for Natural Language Processing (NLP) practitioners who have an intermediate level of knowledge of the Python programming language (especially in the NLP domain) and who are ready to uplevel their NLP skills by applying graph-based tools to their text corpora. To begin these liveProjects, you’ll need to be familiar with the following:
In this liveProject, you’ll learn skills, tools, and techniques for applying powerful graph-based tools to text corpora for effective NLP:
geekle is based on a wordle clone.