Welcome to this machine-learning project repository! I build a predictive model to tackle a real-world challenge which is predicting prices of features houses based on certain features. Follow along as we load and preprocess data, explore insights, and fine-tune our model for accurate predictions.
🔍 Explore Data | 📊 Build Model | 📈 Enhance Performance
- Data Loading and Preprocessing
- Exploratory Data Analysis (EDA)
- Linear and Polynomial Regression
- Cross-Validation for Consistency
- Alternative Models: Random Forest, Gradient Boosting
- Documentation of Findings and Insights
- Clone this repository.
- Follow the step-by-step implementation in
project_implementation.ipynb. - Modify and experiment with code cells.
- Save your final model for future use.
- Pandas
- NumPy
- Matplotlib
- Seaborn
- scikit-learn
📬 Have questions or insights to share? email:floriand.charles@gmail.com