📌 Project Details – HomeSight Team

As the HomeSight Team, we developed an end-to-end data analytics and machine learning solution by combining Excel, Python, Power BI, Streamlit, and advanced modeling techniques.

🔎 Our Workflow

Excel:
Initial data exploration and early insights through descriptive statistics

Python & Machine Learning:

Data cleaning and manipulation using Pandas and NumPy

Data visualization with Matplotlib and Seaborn

Handling missing values and outliers, correlation analysis

Feature engineering (log and scaling transformations)

Model development using multiple algorithms, including:
Linear Regression, KNN, Decision Tree (CART), Random Forest, Gradient Boosting, XGBoost, and LightGBM

Model evaluation using RMSE and R², achieving over 85% predictive accuracy

Power BI:
Design of interactive dashboards with KPI cards, segment-based analyses, and storytelling-driven visualizations

Streamlit:
Development of a web application to present model outputs through a user-friendly interface and enable interactive prediction experiences

📚 Research Support

To strengthen our modeling approach, we reviewed and analyzed three academic research papers and aligned our findings with insights from these studies.

📊 Outcome

The predictions generated by our machine learning models were not only a technical achievement but also provided a strong strategic roadmap for data-driven decision-making.

Through this project, the HomeSight Team enhanced not only technical capabilities but also strategic thinking, discipline, collaboration, and data storytelling skills.