Popular repositories Loading

1. UNDERSTANDING-DEVELOPER-CONTRIBUTIONS-IN-OPEN-SOURCE-SOFTWARE-PROJECTS-AN-EMPIRICAL-ANALYSIS-ACROSS UNDERSTANDING-DEVELOPER-CONTRIBUTIONS-IN-OPEN-SOURCE-SOFTWARE-PROJECTS-AN-EMPIRICAL-ANALYSIS-ACROSS Public

   This project focuses on analyzing and understanding the patterns of developer contributions in the three prominent open-source software ecosystems: NuGet, PyPI, and NPM, all hosted on GitHub.

   1

2. RUSSIA-UKRAINE-REDDIT-USERS-SENTIMENT RUSSIA-UKRAINE-REDDIT-USERS-SENTIMENT Public

   Analyzing Reddit comments to assess public sentiment on Russia and Ukraine following Donald Trump's 2024 election victory. Uses data from the Public Opinion on the Russia-Ukraine War (Updated Daily…

   Jupyter Notebook

3. Marketing-Channel-Analysis-Superstore-Sales. Marketing-Channel-Analysis-Superstore-Sales. Public

   SuperStore collects transactional data but struggles to identify trends. As a data analyst, I analyze customer behavior, marketing, and logistics to provide insights. These help marketing, sales, a…

   Jupyter Notebook

4. Russia-Ukraine-Wars-Streamlit Russia-Ukraine-Wars-Streamlit Public

   Analyzed Reddit sentiment on Russia-Ukraine war (Nov 2024 onwards) using Kaggle data. Tracked trends, key events, and public opinion shifts. Focused on Trump-Zelensky tensions. VADER & Hugging Face…

   Python

5. Israel---Palestine-Reddit-Users-Sentiment-Analysis Israel---Palestine-Reddit-Users-Sentiment-Analysis Public

   This project analyzes Reddit user sentiment on the Israel-Palestine conflict after Donald Trump took office (January 20, 2025). Using daily Reddit comments, I classified user stances (Palestine, Is…

   Jupyter Notebook

6. Loan-Prediction-Streamlit Loan-Prediction-Streamlit Public

   The purpose of using machine learning in this case is to automate the loan application evaluation process by building a predictive model that can classify loan applications into two categories: `Ap…

   Jupyter Notebook