NLP coursework-driven labeling/annotation-style preparation for supervised text learning (inferred from resume coursework only)
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Entity (NER) ClassificationNo explicit paid data-labeling or AI training job experience was stated in the provided resume, but relevant coursework indicates hands-on work with NLP preprocessing and labeling-style targets (e.g., entity-oriented sentiment extraction). The training activities described are consistent with preparing text datasets and deriving labels such as sentiment classes or token-level features for downstream modeling. These tasks typically involve cleaning, transforming, and structuring text to enable supervised learning experiments. • Performed text preprocessing steps such as tokenization and TF-IDF feature creation. • Built/used supervised NLP components like sentiment analysis for label derivation. • Prepared cleaned text inputs suitable for training/evaluation workflows. • Used programming notebooks/tools (Jupyter/Colab) to run experiments and generate labeled training data artifacts.