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mhassan619/README.md


🤖 About Me

I'm a BSCS student at University of Layyah building real, deployed AI systems — not just notebooks.

My work lives at the intersection of LLM engineering, automation pipelines, and backend APIs.
I build tools that solve real problems: RAG chatbots that answer university queries, ML dashboards with live predictions, automation systems that scrape, organize, and act.

class MuhammadHassan:
    role     = "AI Automation Engineer"
    stack    = ["LangChain", "RAG", "FastAPI", "Streamlit", "Groq API", "Python"]
    focus    = ["LLM Apps", "AI Agents", "Automation", "ML Pipelines", "n8n / Flowise"]
    building = "Real products. Not demos."
    belief   = "Consistency beats motivation — every single time."

🚀 Featured Projects — AI & LLM

🤖 UL AI Assistant

LangChain Groq Llama Flask Vercel

Problem: Students at University of Layyah had no instant way to get answers about admissions, departments, and campus info.
Solution: Built a RAG chatbot using LangChain + Groq (Llama 3.1 8B). University data is indexed into a vector store, relevant chunks are retrieved per query, and the LLM generates accurate answers — in both English and Roman Urdu.

🔗 Live App | 📂 Source Code


📄 RAG PDF ChatBot

LangChain Groq RAG Vercel

Problem: Reading long PDF documents to find specific information is slow and inefficient.
Solution: Upload any PDF — the app chunks, embeds, and indexes the content. Ask any question and get precise, context-aware answers using a full RAG pipeline. No hallucinations from generic LLM knowledge.

🔗 Live App | 📂 Source Code


📊 Featured Projects — Machine Learning

📊 Integrated ML Dashboard

Scikit-learn XGBoost Streamlit Pandas

3 production ML models in one live dashboard:

  • 🎓 Student Performance — Classification model predicting academic outcomes
  • 🏠 House Price Estimator — Random Forest regression for real estate valuation
  • 📉 Customer Churn — XGBoost model identifying at-risk customers

🔗 Live Dashboard | 📂 Source


📈 Retail Sales & Weather Analysis

Pandas NumPy Matplotlib Jupyter

Full EDA pipeline correlating retail sales data with weather patterns:

  • Correlation heatmap between weather conditions and sales
  • Rolling window trend analysis + linear regression forecasting
  • From raw CSV to actionable visual insights

📂 Source Code


⚙️ Featured Projects — Automation & Tools

⚙️ AI Automation Dashboard 🗂️ More Tools
Streamlit BS4 GitHub API
Multi-page Streamlit dashboard with 3 integrated tools:
🔍 GitHub Analyzer — Deep profile analytics
🌤️ Weather App — Real-time global weather data
📚 Books Scraper — Structured e-commerce data extraction
File Organizer — Auto local storage cleanup & duplicate handling
News Scraper — Real-time headlines via BeautifulSoup
Student Mgmt System — OOP-based with custom decorators & JSON
PDF Merger — Multi-PDF combining with PyPDF2
Goat Farm OOP System — Real-world OOP project from my own farm 🐐
🔗 Live App | 📂 Source

🧠 Skills

🤖 AI & LLM LangChain Groq RAG Llama 3.1 Ollama Prompt Engineering

⚙️ Automation & Agents n8n Flowise BeautifulSoup4 Selenium File Automation API Integration

📊 Machine Learning Scikit-learn XGBoost Random Forest Feature Engineering Pandas NumPy

🔧 Backend & Deployment Python FastAPI Flask Streamlit Vercel Git C++


📊 GitHub Analytics


🌱 Currently Building Around

AI Agents RAG Systems n8n Workflows FastAPI LeetCode


"Not perfect — just improving every single day."

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