This is a simple and rather inaccurate NLP project which I've made for my AI course. I was tight on time so I have not had the opportunity to build a proper model.
There are many issues with the preprocessing to start with, and the algorithm used to train the model is not ideal, but it was a fun project which gave me the opportunity to learn the basics of NLP.
We're using TF-IDF for vectorizing our preprocessed data, which will be used to train our model using the RandomForestClassifier algorithm.
I've tried this with multiple datasets, yielding 0.6~0.8 accuracy based on the given data. Of course, there were a lot of false positives, and negatives, but the main point was to demonstrate good understanding of NLP (which I hope I was able to demonstrate).