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Rahilshah01/README.md

💫 About Me:

👋 Hi, I'm Rahil Shah
🎓 MS in Data Science Student @ Stevens Institute of Technology


I am an aspiring Data Scientist and Machine Learning Engineer with a passion for turning raw data into actionable insights. Currently, I am seeking full-time opportunities or internships in Data Science, Data Analytics, or Machine Learning.

🌐 Socials:

LinkedIn email

💻 Tech Stack:

Python R Java JavaScript HTML5 C C++ Dart AWS Azure Apache Hadoop nVIDIA Django Flutter OpenCV Streamlit AmazonDynamoDB Postgres MySQL MicrosoftSQLServer SQLite Keras Matplotlib NumPy Pandas Plotly PyTorch scikit-learn Scipy TensorFlow mlflow GitHub Git Docker Kubernetes Power Bi

📊 GitHub Stats:



✍️ Random Dev Quote

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  1. local-med-ai-analyst local-med-ai-analyst Public

    Successfully used Llama 3 to analyze Phase 3 clinical trial data for Suzetrigine (2025).

    Jupyter Notebook

  2. bitcoin-price-forecasting bitcoin-price-forecasting Public

    Financial time-series forecasting of Bitcoin (BTC-USD) using Meta's Prophet library, featuring trend decomposition, seasonality analysis, and 365-day price predictions.

    Jupyter Notebook

  3. customer-churn-prediction-api customer-churn-prediction-api Public

    A production-ready machine learning microservice that uses FastAPI and Docker to serve a Random Forest model for predicting customer churn in real-time

    Python

  4. financial-news-sentiment-analysis financial-news-sentiment-analysis Public

    A specialized NLP pipeline for classifying financial news sentiment into Bullish, Bearish, and Neutral categories. Implements pre-trained transformers (FinBERT) and lexicon-based models to quantify…

    Jupyter Notebook

  5. global-health-wealth-analysis global-health-wealth-analysis Public

    A historical analysis of the 'Preston Curve' using Python to visualize the evolving relationship between global GDP per capita and life expectancy from 1952 to 2007.

    Jupyter Notebook

  6. movie-recommender-system movie-recommender-system Public

    A content-based movie recommendation engine using NLP, CountVectorizer, and Cosine Similarity. Built with Python and deployed via Streamlit.

    Jupyter Notebook