🗂️ Projects
1. House Price Prediction (2022)
Description:
Developed a predictive model for house prices in Ames, Iowa using advanced regression and regularization techniques.
Techniques Used: Ridge, Lasso, Elastic Net, Clustering
Evaluation Metrics: RMSE, MAE
Tools: Python, R
2. Stroke Prediction System (2022)
Description:
Designed a machine learning model to predict stroke risks using a Kaggle dataset. Identified key controllable factors for early detection.
Techniques Used: Logistic Regression, Gaussian Naive Bayes, Decision Tree, Random Forest, SVM
Evaluation Metrics: Accuracy, F1 Score
Tools: Python, R
3. Bank Marketing Analysis (2023)
Description:
Analyzed bank marketing campaign data to predict term deposit subscriptions.
Techniques Used: Correlation Heatmaps, Decision Trees, Random Forest, XGBoost, K-Nearest Neighbors
Outcome: Identified main client attributes influencing term deposit acceptance
Tools: Python, R