real-world-dataset

Google Maps–Inspired AI Traffic Route Guidance | Deep Learning + Heuristic Search | Real-World SCATS Data (Boroondara 2006)

Develop a predictive model to accurately forecast hourly traffic volumes at different road junctions based on historical traffic data

This project uses advanced Excel to analyze real-world global data job postings, uncovering insights on salary trends, in-demand skills, and market patterns.

Statistical analysis of NYC TAP funding across colleges using Python, EDA, hypothesis testing, and real 260K-row dataset.

Data-driven market analysis of Swiggy restaurants to uncover top cuisines, delivery efficiency trends, and high-opportunity areas for new restaurant entry.

An end-to-end analysis of Google Pay India Play Store reviews to uncover reliability issues, user sentiment patterns, and support performance.

Built a machine learning pipeline to detect fraudulent credit card transactions using real-world data (1M+ rows). Explored fraud patterns, validated key hypotheses, and optimized models like KNN, Random Forest, and SVM with 98%+ recall. Strong focus on data insights & impact.

End-to-end market and restaurant analysis using Zomato data (123K+ records), focusing on city-wise competition, pricing, ratings, cuisines, and delivery trends using Python.

Machine Learning Projects using Python | End-to-End ML workflows including data preprocessing, exploratory data analysis, model building, and evaluation on real-world datasets.

Exploratory Data Analysis of a ride-hailing dataset uncovering cancellation patterns, demand trends, operational delays (TAT), revenue drivers, and customer experience insights using Python, Pandas, Seaborn, and Matplotlib.