This paper aims to predict which of the South African presidents between 1994 and 2022 might have said a specific sentence during their SONA address. It leverages various text transformation techniques, such as Bag of Words (BoW), Term Frequency-Inverse Document Frequency (tf-idf), and text embeddings (a very simple embedding as well as BERT). Subsequent application of machine learning models, including a feed-forward neural net, Support Vector Machine (SVM), Naive Bayes, and a BERT classification model, offers a comparative lens to evaluate the efficacy of each approach.
Link to the website: https://jared-t.github.io/DS4I_Ass1Code/