This series of notebooks is aimed at helping fellow NLP enthusiasts think about applying new tools and techniques to practical tasks. My goal is to keep the code and work flow simple, and focus on an actual use case.
Sentiment analysis is a fairly common task in machine learning. Hugging Face's new pipeline feature, however, has made it incredibly easy to use a transformer-based model for this task. In this notebook, I'll explore how the HF pipeline can be used together with Plotly and Google Sheets to produce a detailed analysis of one speech, as well as how the same technique can be adapted for longer-term analysis of political speeches on one topic, or those by a common group of speakers.
Fuller background in this post here.