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huscse/README.md

Hi there, I’m Husnain πŸ‘‹

Profile Banner

πŸ‘¨β€πŸ’» About Me

πŸŽ“ Senior at Brooklyn College, majoring in Computer Science
πŸ”­ Aspiring Software / Machine Learning Engineer

I’m a Computer Science student and emerging SWE/ML Engineer passionate about Artificial Intelligence, Machine Learning, and Software Development. I love creating impactful applications that solve real-world problems and provide meaningful user experiences.

  • 🌱 Currently building AI-powered tools, web applications, and ML models to tackle real-world problems
  • πŸ’Ό Open to internships in Software Engineering, AI/ML
  • πŸ“š Continuously improving my DSA, full-stack development, and ML skills
  • ✨ Dedicated to writing clean, scalable, and well-documented code

πŸ“« Reach Me At: LinkedIn: https://www.linkedin.com/in/husnain-kh


πŸš€ Projects

  • Overview: Applied machine learning to predict Airbnb listing prices in New York City, following the full ML lifecycle.

  • Tech Stack: Python, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Jupyter Notebook

  • Highlights:

    • Complete end-to-end regression pipeline for real-world price prediction
    • Built and evaluated Linear Regression and Tuned Random Forest models
    • Achieved ~17% improvement in RMSE using Random Forest over baseline
    • Identified top features influencing price like accommodates, bathrooms, and room_type
    • Visualized residuals, actual vs predicted prices, and feature importances

  • Overview: A tool that generates custom AI-powered flashcards to help students learn faster and smarter.

  • Tech Stack: Next.js, Tailwind CSS, Firebase, OpenAI API, Material UI, Clerk, Stripe

  • Highlights:

    • Generate personalized flashcards from any topic or document
    • Supports a premium version (PromptWise Plus) for advanced features
    • Clean, responsive UI with modern animations
    • Firebase-based authentication and data storage

  • Overview: Your personal companion for discovering Quranic guidance tailored to your heart’s needs.

  • How It Works:

    • Select how you’re feeling, joyful, anxious, grateful, or seeking guidance
    • Receive carefully selected verses that speak directly to your current state
    • Experience peace and tranquility through divine guidance
  • Tech Stack: Next.js, Tailwind CSS, React

  • Highlights:

    • Emotion-based Quranic recommendations
    • Interactive user-friendly interface
    • Mobile-ready design for spiritual guidance on the go

πŸ“ˆ GitHub Stats


πŸ›  Languages and Tools


Feel free to reach out β€” I’m always open to collaborating, learning, and building cool stuff! πŸš€

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  1. vlm-dataset-navigator vlm-dataset-navigator Public

  2. ecornell-project ecornell-project Public

    Predicting Airbnb listing prices in NYC using machine learning with data cleaning, EDA, and Random Forest regression.

    Jupyter Notebook

  3. Spam-Mail-Prediction Spam-Mail-Prediction Public

    A machine learning project that classifies emails as Spam or Ham based on their content. The dataset is preprocessed, split into training/testing sets, and trained using a Logistic Regression model…

    Jupyter Notebook