Explore the potential of feature engineering and hyperparameter tuning in improving text classification models for identifying abusive content online. Delve into feature extraction, selection, construction, and the bag-of-words (BOW) approach. Examine character- and word-level representations, term frequency-inverse document frequency (TF-IDF), tokenization, stopwords, and stemming. Learn about Support Vector Machines (SVMs), their hyperparameters, and tuning techniques, such as grid and random searches. Understand the role of feature engineering in boosting the performance of hate speech detection algorithms and SVMs.
