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bengaluru

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Exploratory Data Analysis (EDA) on Bengaluru restaurant data to uncover insights into ratings, cuisines, cost, location, and dining trends. Built using Python, Pandas, Seaborn, and Matplotlib to understand customer behavior and food business patterns.

  • Updated Jul 8, 2025
  • Jupyter Notebook

A data-driven dashboard for Bengaluru that maps BMTC bus stops, metro stations, and BBMP zones to analyze public transport accessibility. It computes key metrics like access coverage, first/last-mile gap index (FLGI), bus stop density, and nearest-metro distance—helping planners identify weak spots and prioritize investments

  • Updated Aug 23, 2025
  • Python

End-to-end Machine Learning project to predict Bengaluru house prices using Linear Regression. Features comprehensive data cleaning, advanced preprocessing, exploratory data analysis, feature engineering, and cross-validation, achieving strong performance (R² ≈ 81%)

  • Updated Feb 14, 2026
  • Jupyter Notebook

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