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Samsung PRISM
Research & Development InternMar 2025 - Aug 2025
Bengaluru · Hybrid100K+
Records
3
ML Projects
5+
Models Evaluated
Mar–Aug 2025
Term
- •Projects: Completed three machine learning projects, each involving 100K+ records, covering data collection, preparation, model development, evaluation and prediction
- •Workflows: Developed Python-based data processing workflows for business requirements by cleaning, organizing and processing datasets and applying classification and regression models
- •Evaluation: Compared Random Forest, XGBoost, CatBoost, Ridge and LightGBM using accuracy, precision, recall and RMSE to evaluate model performance across multiple use cases
- •Inference: Built, debugged and tested end-to-end ML inference workflows connecting processed data with model predictions for real-time business applications
PythonMachine LearningClassificationRegressionXGBoostCatBoostRandom ForestLightGBMRidgeData Processing