🏠📉 Housing Prices & Bike Sharing Analytics

This dual-topic project combines Python for data preparation and machine learning, and Power BI for dashboard creation. The two datasets explored:

• Housing Prices: Feature engineering and regression models to predict house sale prices.
• Bike Sharing: Time-based and environmental factors influencing daily bike rental demand.

🔬 Python Workflow

• 🧹 Data Cleaning and Feature Selection
• 📊 EDA and Outlier Treatment
• 🤖 Regression Models (Linear Regression, XGBoost, Random Forest)

📊 Notebooks:

📘 View Notebook Housing Prices – Data Prep

📘 View Notebook Housing Prices – Prediction

📘 View Notebook Bike Sharing – Data Prep

📘 View Notebook Bike Sharing – Prediction

📊 Power BI Dashboards

Complementary dashboards display model results and trends using filters and visuals for stakeholders.

📈 Trend of house prices by condition and location

🚲 Bike demand segmented by weather and working days