A Machine Learning approach to estimate the likelihood of road accidents based on road, weather, and environmental conditions

This is a traffic severity prediction model built using XGBoost, deployed on flask.

Dashboard of road accidents occured during the period of 2021-22 with different reasons behind. Using Ms excel for the data processing and creating pivot tables , using fucntions and may more features of excel to create the final dashboard to give quick overview of data

Interactive Excel dashboard analyzing UK road accident data for 2021–2022 (307K+ records)

This project aims to analyze road accidents based on factors like weather, road surfaces, location, vehicle type, and casualties. I extracted, cleaned, analyzed the data, and built an interactive dashboard for easy visualization. The insights gained will aid in accident prevention and improving road safety.

Excel dashboard analyzing road accident patterns, casualty severity, road conditions, and environmental factors using pivot tables and slicers.

Road accident data analysis project with interactive Tableau dashboard to identify patterns, severity trends, and safety insights.

🚦 Excel-based interactive dashboard analyzing road accident data to uncover insights on accident severity, vehicle types, and road conditions using data visualization techniques.

This repository contains Tableau visualization projects focused on data analysis across different domains. Projects include: 1. IPL Visualization - Insights into IPL match, Team and player statistics. 2. EV Analysis - Visualizations exploring the adoption of electric vehicles. 3. Road Accident Analysis - Analysis of road accident patterns

Machine learning project done during Monsoon Semester 2023 in IIITD.

This project features an Excel-based interactive dashboard that visualizes comprehensive road accident data. The dashboard provides insights into fatal, serious, and slight casualties, along with detailed breakdowns by road type, surface conditions, light conditions, vehicle types, and geographical areas.

Exploratory Data Analysis (EDA) Project on Road Accidents for Semester 4 - CSE

In-depth Excel-driven exploration of road accident statistics — analyzing severity levels, environmental factors, and temporal patterns through dynamic dashboards, performance metrics, and interactive visuals. Perfect for Excel analytics learners and professionals aiming to enhance data visualization and road safety analysis skills.

Machine Learning-based system that predicts optimal ambulance deployment locations using accident data analysis and clustering techniques to reduce emergency response time and improve emergency healthcare services.

A complete Excel-based Business Intelligence Dashboard built to analyze road accident patterns, severity, and risk factors using detailed accident records. This project transforms raw data into actionable insights that can help traffic authorities, researchers, and data analysts understand the causes behind accidents and plan safety interventions.

Interactive Power BI dashboard to analyze road accidents, identify risk factors, and uncover geographic hotspots for safer roads.

This project analyzes road accident data in the UK using Tableau. It provides insights into casualties, accident severity, vehicle types, road conditions, and geographical distribution. The dashboard helps stakeholders identify trends and make data-driven decisions to improve road safety.

Road Accident Dashboard built in Microsoft Excel. Includes data cleaning, pivot tables, KPIs, and interactive visuals i.e., donut charts, trends, timeline slicers. Demonstrates transforming raw accident data into actionable insights for portfolio and data analytics practice.

Developed an interactive Road Accident Analysis Dashboard in Microsoft Excel using Pivot Tables, Pivot Charts, and Slicers to analyze 896K+ casualties by severity, vehicle type, road conditions, and yearly trends. Enabled dynamic filtering and year-over-year comparison to support data-driven decision-making.