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maroofiums/README.md

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Hi there, I'm Maroof

I am an AI/ML developer focused on building strong foundations in mathematics, backend systems, and applied machine learning. My goal is to understand how core concepts in math and computer science translate into real-world applications and to use that understanding to build practical, efficient, and scalable systems. I spend most of my time learning and strengthening fundamentals rather than rushing into advanced tools, because I believe strong basics lead to long-term growth. I am currently improving my skills in Python programming, data structures, and problem-solving while also studying key mathematical areas like linear algebra, probability, and calculus, which are essential for understanding machine learning models. Alongside this, I am learning backend development concepts such as APIs, databases, and system design to understand how full applications are built and deployed. In machine learning, I am exploring both theory and implementation by working on small projects, experimenting with models, and learning how training and evaluation processes work. My interest lies in connecting all these areas math, machine learning, and backend engineering to build complete, real-world AI systems. My long-term goal is to become a skilled AI engineer who can design, develop, and deploy intelligent solutions. I am continuously learning, practicing, and improving every day with consistency and discipline.

  • ๐ŸŽ“ Studying Software Engineering at MITI (expected graduation: Oct 2026)
  • ๐Ÿ”ญ Currently building Velox and progressing through my ML roadmap
  • ๐Ÿง  Currently learning Computer Vision, DSA, MLOps, and Reinforcement Learning
  • ๐ŸŒ Based in Karachi, Pakistan
  • ๐Ÿ’ฌ Ask me about building AI pipelines, RAG systems, and scalable FastAPI backends
  • ๐Ÿ“ซ Reach me at maroof96965@gmail.com
  • ๐Ÿ–ฅ๏ธ Portfolio maroofiums.vercel.app


๐Ÿ“Œ About Me

  • ๐ŸŒฑ I'm currently learning Machine Learning, Deep Learning, and System Design
  • ๐Ÿ‘ฏ I'm looking to collaborate on real-world AI/ML and FastAPI backend projects
  • ๐Ÿค I'm looking for help with scalable ML systems and production-level deployment
  • ๐Ÿš€ I enjoy building end-to-end AI systems from data to deployment

๐Ÿง  My Focus Areas

  • Machine Learning & Deep Learning
  • Backend Development (FastAPI)
  • MLOps & Model Deployment
  • Data Science & Analytics
  • Open Source Contribution

๐Ÿ“Š GitHub Stats


๐Ÿ“ˆ Contribution Activity


๐Ÿ”ฅ Streak Statistics


๐Ÿ“… Contribution Calendar


๐Ÿ› ๏ธ Languages & Tools

๐Ÿ’ป Programming Languages


๐ŸŽจ Frontend


โš™๏ธ Backend


๐Ÿ“Š Data Science & ML


๐Ÿค– Deep Learning / AI


๐Ÿ“ˆ BI / Analytics


๐Ÿ—„๏ธ Databases


โ˜๏ธ DevOps & Cloud


๐Ÿงฐ Tools


๐Ÿ”— Connect With Me


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  1. Movies_Recommended_System Movies_Recommended_System Public

    A hybrid movie recommendation system that combines content-based filtering (overview, genres, tagline) with popularity and vote average to provide smarter, personalized movie suggestions. The app dโ€ฆ

    Jupyter Notebook

  2. Sentiment-Dashboard Sentiment-Dashboard Public

    A Streamlit dashboard that performs real-time and batch sentiment analysis using pretrained Hugging Face Transformers. Users can analyze single texts or CSV files and explore results via interactivโ€ฆ

    Jupyter Notebook

  3. News-Topic-Classification-using-BERT News-Topic-Classification-using-BERT Public

    Fine-tuned a BERT model to classify news headlines into World, Sports, Business, and Science & Technology. Preprocessed AG News dataset, trained the model, and achieved ~93.7% accuracy. Deployed viโ€ฆ

    Jupyter Notebook

  4. Fake-News-Detection Fake-News-Detection Public

    Detect whether news articles are REAL or FAKE using a pretrained transformer model. Deployed as a Streamlit app for real-time predictions with confidence scores. No training required, works on any โ€ฆ

    TypeScript

  5. AI-Resume-Screening-Platform AI-Resume-Screening-Platform Public

    A production-ready full-stack platform for semantic resume screening using Django, DRF, React, and AI embeddings. Features resume parsing, candidate-job matching, JWT authentication, role-based accโ€ฆ

    TypeScript

  6. AI-Research-Assistant AI-Research-Assistant Public

    AI Research Assistant is a RAG system using FastAPI, LangChain, ChromaDB, and Mistral AI. It lets users upload PDFs, stores embeddings, retrieves relevant chunks via semantic search, and generates โ€ฆ

    Python