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Data Science and AI Engineer
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Data Science and AI Engineer
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SURESHBEEKHANI/README.md

Suresh Beekhani

Helping Global Businesses Automate with AI | ML, DL, NLP, LLMs, Agentic & Generative AI | RAG | AWS | LLM Fine-Tuning | Remote Consultant

🌍 About Me

I design and deploy production-grade AI systems that move businesses from experimentation to automation.

With 4+ years of hands-on AI engineering experience, I specialize in building scalable, secure, and intelligent systems that deliver measurable impact across industries.

✔ 40+ AI Models Built
✔ 25+ Production Deployments
✔ Finance, Healthcare & E-Commerce Expertise
✔ Remote AI Consultant (Global Clients)

🧠 Core Expertise

🔹 Artificial Intelligence

  • Machine Learning (ML)
  • Deep Learning (DL)
  • Natural Language Processing (NLP)

🔹 Generative & Agentic AI

  • LLM Systems & Fine-Tuning
  • Retrieval-Augmented Generation (RAG)
  • Autonomous AI Agents
  • Multi-Agent Architectures
  • Context & Memory Systems

🔹 Production & Cloud

  • FastAPI, Docker
  • CI/CD (GitHub Actions)
  • MLflow
  • AWS Cloud Infrastructure
  • Scalable API Architecture

💼 Professional Background

🏢 Upwork – AI & Machine Learning Specialist
🎓 Sir Syed University of Engineering & Technology (SSUET)
📍 Karachi, Sindh, Pakistan
🌐 Portfolio: https://sureshbeekhani.netlify.app/
📧 Email: sureshbeekhani26@gmail.com

📊 GitHub Performance

🎯 Mission

To help global companies build AI systems that:

• Understand
• Reason
• Act
• Deliver measurable business outcomes

⭐ Open to collaborations, consulting, and enterprise AI partnerships.

Pinned Loading

  1. Movie-Recommender-System Movie-Recommender-System Public template

    This guide provides a step-by-step approach to implementing a content-based filtering system for movie recommendations. Each section includes specific tasks and example code to illustrate the process.

    Jupyter Notebook 1

  2. Chat-with-Postgres-SQL Chat-with-Postgres-SQL Public

    This Streamlit app enables users to query a MySQL database using natural language. It translates questions into SQL, executes them, and returns the results in plain language. Powered by LangChain …

    Python 1

  3. RAG_With_Knowledge_Graph RAG_With_Knowledge_Graph Public

    RAG_With_Knowledge_Graph enhances customer support using Retrieval-Augmented Generation (RAG) and a knowledge graph. It leverages Neo4j for structured data, LangChain for retrieval, and Google Gene…

    Jupyter Notebook 1