Project 17-Urban_ Logistics _Demand_Forecasting

[sahithipinnam]

Adding Project 17- Urban logistics demand forecasting for pull request.

This project focuses on Urban Logistics Demand Forecasting (Project 17) using Melbourne Transport Activity Counts data. The work completed so far includes:
• Performed Exploratory Data Analysis (EDA) to understand dataset structure and logistics-related activity patterns
• Combined multi-year datasets (2023–2026) into a single dataset for analysis
• Conducted data cleaning and preprocessing, including handling missing values and formatting date-time features
• Filtered logistics-related vehicle types such as vans and trucks for demand forecasting
• Created time-based features (hour, day, weekday/weekend) for temporal analysis
• Conducted temporal analysis to identify logistics demand trends over time
• Performed spatial analysis using location coordinates to understand geographic demand distribution
• Derived initial insights to support future demand forecasting using machine learning models

[YuvaraniD]

Hi @sahithipinnam , great work on this use case! The structure, visualisations, and insights are clear and well-presented .
Just one minor note for future improvement:

• Please ensure Australian English is used consistently throughout the notebook.

Nice work overall!