Sai Charann B

Designed and executed end-to-end ML workflows (data ingestion → preprocessing → model training → evaluation) on real-world datasets using Python and Scikit-learn, mirroring industry AI development lifecycle practices. Performed comprehensive data preprocessing — missing value imputation, duplicate removal, feature scaling, and feature engineering — to prepare production-ready datasets for ML pipeline ingestion. Built, evaluated, and compared multiple supervised and unsupervised models; analysed performance using accuracy, precision, recall, and F1-score metrics and generated visual reports to communicate findings. Documented experiments and maintained reproducible code in Jupyter Notebooks and Git, following professional AI engineering standards.