1. Credit Card Fraud Detection

• Algorithm Used: Logistic Regression 

• Description: Developed a binary classification model to detect whether a credit card transaction is fraudulent or legitimate.

2. Wine Quality Prediction

• Algorithm Used: Random Forest Classifier

• Description: Built a classification model to predict whether a wine sample is of good quality or bad quality based on its physicochemical properties.

3. Loan Status Prediction

• Algorithm Used: Support Vector Machine (SVM)

• Description: Designed a predictive model to determine whether a loan application is approved or not approved.

4. House Price Prediction

• Algorithm Used: XGBoost Regressor (XGBRegressor)

• Description: Implemented a regression model to estimate house prices by comparing actual market values against predicted values.

5. Car Price Prediction

• Algorithm Used: Linear Regression / Lasso Regression

• Description: Created a regression-based pricing model to predict the market value of cars using historical vehicle attributes.

6. Big Mart Sales Prediction

• Algorithm Used: XGBoost Regressor (XGBRegressor), Label Encoding

• Description: Developed a sales forecasting model to predict outlet product sales performance using store and product-related features.

7. Heart Disease Prediction

• Algorithm Used: Logistic Regression

• Description: Built a healthcare classification model to determine whether a person is at risk of heart disease or healthy based on medical indicators.

8. Customer Segmentation using K-means Clustering

• Algorithm Used: K-Means Clustering

• Description: Performed unsupervised learning to group customers into distinct behavioral and purchasing segments for market analysis

9. Rock vs. Mine Prediction

• Algorithm Used: Logistic Regression

• Description: Developed a sonar signal classification model to identify whether the detected object is a rock or a mine.

10. Medical Insurance Cost Prediction

• Algorithm Used: Linear Regression

• Description: Created a predictive analytics model to estimate medical insurance charges based on personal and health-related factors.

11. Diabetes Prediction

• Algorithm Used: Support Vector Machine (SVM)

• Description: Designed a medical diagnostic model to classify whether an individual is diabetic or non-diabetic.

12. Penny Mint Analysis

• Algorithm Used: Support Vector Machine (SVM)

• Description: Built a classification model to determine whether a penny coin was minted in Denver or Philadelphia based on image and feature analysis.