Data Science Intern
Current- Employed advanced statistical models such as Logistic Regression, XGBoost, Random Forest, MLP, DNN to predict cow pregnancy probabilities, achieving a 15% performance boost through adept handling of imbalanced data and.
- Conducted in-depth exploratory data analysis, preprocessing, and feature engineering on a dataset of 26,000 cow records, refining model accuracy.
- Successfully implemented hyperparameter tuning and 10-fold cross-validation, resulting in exceptional outcomes such as an AUC of 0.85 and an F1 score of 0.87 using the XGBoost classifier.