Here, we have used the user's feedback data and content data to solve the content recommendation problem.
For unbalanced Twitter data, XGboost outperformed the LSTM, AutoGluon, and ULMFiT models on hate speech detection with an F1 score of 0. 75 compared to 0. 38 and 0. 37, and 0. 38 respectively.
Natural Language Processing (NLP) is increasingly used as a key ingredient in critical decision-making systems such as resume parsers used in sorting a list of job candidates.