Projects

Predictive Health Analysis Using Machine Learning (Heart Disease Prediction)

(Role: Project Lead and group collaborator)

This collaborative project, undertaken by a team of five, successfully developed a highly accurate machine-learning model with 98.25% accuracy for predicting heart disease, leveraging detailed analysis of health conditions and lifestyle factors from the dataset. Additionally, the project delivered interactive Tableau dashboards, providing stakeholders with actionable insights into critical risk factors.The success of this project demonstrates the effectiveness of strong leadership, meticulous planning, and seamless teamwork in delivering innovative solutions to complex healthcare challenges.

Project Links for GitHub and Tableau

• GitHub
• Tableau

• Skills

Python, SQL, Sklearn, Machine Learning, Random Forest Classifier, Support Victor Machine, and Neural Network

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Customer Churn Analysis Through Data Visualization: Unlocking the Secrets to Customer Loyalty

(Role: Sole Author)

This project conducts an in-depth analysis of factors influencing customer churn, including high monthly rates, total charges, gender, streaming TV usage, senior citizenship, contract types, and internet services.This analysis helps businesses identify key drivers of customer churn, enabling them to implement targeted strategies to improve retention, optimize pricing, and tailor services to better meet customer needs, ultimately enhancing customer satisfaction and profitability.

Project Link for GitHub

• GitHub

• Skills

Microsoft Excel, Python, NumPy, Pandas, Matplotlib, Seaborn.

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Crowdfunding Data Optimization: Enhancing Accuracy and Reliability Through Data Cleaning

(Role: Group Collaborator)

This project enhanced data analysis readiness by developing an efficient data cleaning process and an ETL pipeline using Python's Pandas, NumPy, and Regex for data transformation. The cleaned and transformed data was seamlessly integrated into a Postgres database, ensuring accessibility for advanced analytics.By automating data processing and improving accuracy, the project enables businesses to make data-driven decisions faster, reduce manual effort, and enhance operational efficiency, ultimately driving more informed strategies and improved performance.

Project Link for GitHub

• GitHub

• Skills

Microsoft Excel, Python, Pandas, NumPy, Regex for data transformation, and SQL

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Seasonal Insights: Analyzing Citibike Usage Trends and Behaviors in Winter and Summer 2023

(Role: Sole Author)

This Tableau project analyzed Citibike usage data to uncover seasonal trends, station preferences, and user demographics. An interactive dashboard was developed to visualize insights, showcasing how weather and seasonal changes influence urban mobility and bike-sharing patterns.These insights can help businesses optimize bike availability, strategically plan station locations, and design targeted marketing campaigns, ultimately enhancing user satisfaction and maximizing operational efficiency.

Project Link for Tableau

• Tableau

• Skills

Tableau, Excel, Python, Data Cleaning, Data Visualization, and Story-telling.

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Crowdfunding Data Optimization: Enhancing Accuracy and Reliability Through Data Cleaning

(Role: Sole Project)

This project analyzes the dynamics of crowdfunding campaigns using a dataset of 1,000 sample projects from platforms like Kickstarter and Indiegogo, aiming to identify trends and factors driving campaign success.The insights generated can help businesses optimize their crowdfunding strategies, improve campaign planning, and enhance engagement with backers, ultimately increasing the likelihood of successful funding and project execution.

Project Link for GitHub

• GitHub

• Skills

Microsoft Excel, PivotTables, VLOOKUP, Filters, Sum if(s), Index (Match), Conditional Formatting, and Text to Column

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