Building an End-to-End Sentiment Analysis Pipeline with Scikit-LLM (opens in new tab)

Traditional machine learning pipelines for predictive tasks like text classification usually rely on extracting structured, numerical features from raw text — for instance, TF-IDF frequencies or token embeddings — to feed into classical models such as logistic regression, ensembles, or support vector machines.