Pavitr Swain

💡 Heart Disease Analysis & Prediction This project explores heart disease data using data visualization, correlation analysis, and statistical insights with Python. Includes cleaned datasets and interactive Colab execution.

A machine learning project that detects stress levels in social media posts (Twitter & Reddit) using NLP, sentiment analysis, and machine learning models. 📌 Tech Stack: Python, Sklearn, NLP, NLTK, TF-IDF, Sentiment Analysis, Random Forest, Logistic Regression, Data Visualization 📌 Dataset: Kaggle Stress Data

Performed EDA on PowerCo’s customer and pricing data to identify key patterns, analyze churn factors, and visualize data distributions.🛠 Tools Used ✅ Python (Pandas, Matplotlib, Seaborn) ✅ Jupyter Notebook 🚀 Next Steps: Feature engineering & churn prediction modeling.