I am a Third-Year B.Tech Student (CSE - AI & ML) at Pimpri Chinchwad University and an IoT Club Treasurer. I specialize in building intelligent data retrieval systems (RAG), scalable AI pipelines, and decentralized applications.
- π Selected for: Samsung Innovation Campus Program (2025).
- π± Currently exploring: Advanced RAG optimizations and Multi-Agent Systems.
- π― Open to collaboration on: AI-driven Data Science projects and Web3 integration.
| Domain | Technologies |
|---|---|
| Languages | Python, Java, C++, SQL, Solidity |
| AI & ML | Scikit-learn, Pandas, PyTorch, TensorFlow, LangChain, HuggingFace |
| Backend & Tools | Git/GitHub, Flask, Docker, Linux, Postman |
| Databases | MongoDB, PostgreSQL, Vector Databases (ChromaDB) |
| Project | Description | Stack |
|---|---|---|
| Brain Tumor Detection using ML & Blockchain | Secure Medical Diagnostics via Blockchain A hybrid framework merging Random Forest classification with the Ethereum Sepolia blockchain. Anchors dataset hashes on-chain to ensure immutable data provenance and verifiable model integrity. |
Python, Scikit-learn, Solidity, Ethereum, Sepolia Testnet |
| CodeAssist Extension | Offline AI Coding Assistant Lightweight VS Code extension integrating a local LLM (TinyLlama via Ollama). Provides an interactive chat, copyable code blocks, and full offline privacy without API costs. |
JavaScript, Ollama, VS Code API |
| Pune House Pricing | End-to-End Real Estate Estimator Deployed a Random Forest model via Flask to predict housing prices. Engineered custom features to handle severe data sparsity (69% accuracy) and identify valuation drivers. |
Python, Flask, Scikit-learn, HTML/CSS |
- LinkedIn: linkedin.com/in/prathameshnavale18
- Email: workwithprathamesh18@gmail.com
