A collection of applied machine learning projects built in Python, covering real-world prediction tasks across finance, health, marketing, and forecasting.
- Weather Prediction (XGBoost)
- Wine Quality Classification
- Stock Price Prediction (Regression)
- Cancer Diagnosis (Classification)
- Marketing Analytics
- Taxi Fare Prediction (ANN – TensorFlow/Keras)
- Python
- Scikit-learn
- XGBoost
- TensorFlow / Keras
- Cross-validation & GridSearchCV
- Performance metrics (MAE, RMSE, Accuracy)
Each notebook contains data preprocessing, feature engineering, model training, hyperparameter tuning, and evaluation.