Python-Based Data Processing and Annotation Pipeline for NLP Dataset
Our team developed a Python-based data processing and labeling pipeline to prepare high-quality datasets for training Natural Language Processing models. The project involved building automated scripts to collect, preprocess, and structure large volumes of text data before annotation. Python libraries were used for text cleaning, tokenization, and dataset preparation.