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DecodingAzero/README.md

💫 About Me:

Hey, it's Maharnav,

I build systems at the intersection of Machine Learning, Natural Language Processing, Computer Vision, and Large Language Models.

Over the last few years, I have worked on projects involving:

• Fine-tuning Llama 3 (8B) using QLoRA + PEFT
• Building Hybrid RAG pipelines with FAISS + Gemini API
• Designing semantic search engines for healthcare information retrieval
• Developing AI-based computer vision systems for flood depth estimation and urban monitoring
• Working with low-resource NLP systems including language modeling and text generation

Areas I work in

LLM Engineering
Retrieval Systems (RAG / Vector Databases)
NLP Systems Design
Applied Computer Vision
AI Research Engineering

🌐 Socials:

email

💻 Tech Stack:

Python C JavaScript Java MySQL MongoDB Canva Adobe Lightroom Adobe Keras Matplotlib mlflow NumPy Pandas PyTorch scikit-learn Scipy TensorFlow Git GitHub Notion Meta Epic Games Ubisoft Steam nVIDIA Unreal Engine Riot Games OpenCV

📊 GitHub Stats:



✍️ Random Dev Quote

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  1. dual-architecture-culinary-ai dual-architecture-culinary-ai Public

    Dual-architecture AI recommendation system combining fine-tuned Llama 3 (QLoRA) and Hybrid RAG with FAISS + Gemini to generate context-aware, hallucination-resistant culinary recommendations.

    Jupyter Notebook 1

  2. clinical-semantic-search-faiss clinical-semantic-search-faiss Public

    Semantic search engine for medical literature using MiniLM embeddings, FAISS vector indexing, and dense retrieval for fast, hallucination-free clinical information retrieval.

    Jupyter Notebook 1

  3. smart-expense-tracker smart-expense-tracker Public

    A RESTful expense management API built with FastAPI featuring JSON persistence, request validation, automated testing, and interactive Swagger documentation.

    Python