Exploring Airbnb Market Trends

This project involves analyzing Airbnb listings by employing Python libraries like Pandas and NumPy. It highlights the process of data loading, merging, cleaning, and extracting key insights, showcasing the practical application of data manipulation.

Modelling Car Insurance Claim Outcomes

The project focuses on creating a scalable, user-friendly platform for real-time data analysis and visualization, incorporating machine learning for trend prediction and insights, aimed at facilitating quick and informed decision-making.

Market Analysis for Fitness Studio

This project analyzes global and MESA region interest in different workouts, identifying top countries and comparing yoga and zumba popularity in two countries. It highlights fitness trends and changes due to COVID-19.

Predicting Credit Card Approvals

This project optimizes a logistic regression model for better prediction accuracy in finding credit card approvals. It employs GridSearchCV to fine-tune model parameters, aiming to enhance decision-making processes with more precise outcomes.

The City that Never Sleeps

The big data project aimed to analyze a large dataset consisting of parking tickets from New York City in 2020-21 to provide insights and recommendations for four different stakeholders. The project uses Hadoop and Spark to manage the processing of massive amounts of data.

The Buzz Behind the Buzz

In this project, I performed a simulation of working as a Data Analyst for Accenture, analysing Social Media Data from Social Buzz, to provide insights and recommendations.

Customer Segmentation of a Brazilian e-commerce business

The analysis behind this project is part of a business investigation that is focused on supporting Olist’s business objectives. These are: Attracting more shopkeepers by increasing the service and grabbing attention of more end-customers through a broader product spectrum and higher satisfaction.

Stock Prediction and Visualization

In this project, the team will be creating a website which displays stock predictions as charts, along with the company description, stock price patterns and indicators. The stock predictions will be done using Support Vector Regression (SVR) technique and data from the yfinance library.

Loan Eligibility Prediction

This paper explores the use of Machine Learning Algorithms for loan default prediction using financial and personal data. It preprocesses the data and trains various algorithms to identify the most suitable one.

Skybound Loyalty

In this simulation project for British Airways, I leveraged web scraping to gather consumer data, performed in-depth analysis, and built a predictive model to enhance customer retention during holiday seasons. By identifying key factors influencing loyalty, the model provides data-driven strategies

Powering Retention

In a BCGX simulation, I analyzed client data to determine if price sensitivity was the key driver of customer churn in a power company. Leveraging machine learning, I developed a Random Forest predictive model to assess churn risk, uncovering critical factors beyond pricing. To drive business impact

Optimizing Retail Success: Analyzing Store Layout Impact on Customer Sales

In this project for Quantium, I analyzed transaction and customer data to assess how trial store layouts influenced sales. The insights helped identify trends and optimize store design for better customer experience and revenue growth.