Machine Learning Trainee, Data Labeling for Structured Data Classification
During my time as a Machine Learning Trainee at SHAI, I built end-to-end machine learning workflows focused on structured data processing and model development. I performed data exploration, feature engineering, and created visualizations to interpret and support model analysis. My work involved labeling data for training and validating various classification and prediction models. • Processed structured datasets to prepare labeled inputs for machine learning workflows. • Labeled text and structured data for use in random forest, gradient boosting, and ensemble models. • Conducted manual validation of data splits and model outputs to ensure proper classification. • Employed tools such as Pandas, NumPy, and Scikit-learn to facilitate data labeling and feature annotation.