🎓 CS Graduate (Data Science) · ⚙️ AI Engineer · 💻 Full-Stack Developer
I build intelligent systems that go beyond demos — from fine-tuned LLMs and RAG pipelines to full-stack web apps that actually ship. I'm driven by one question: how can AI solve problems that matter?
- 🎓 B.Tech in Computer Science & Engineering (Data Science).
- ⚙️ Passionate about AI Engineering — designing and deploying intelligent systems from model to production.
- 🤖 Building AI-powered apps with Python, TensorFlow, Scikit-learn, RAG, Llama 3.2 & ChromaDB.
- 💻 Full-Stack Developer skilled in Software Engineering, Data Analytics & Machine Learning.
- 🌱 Currently exploring LLM fine-tuning, agentic AI & scalable AI system design.
- 🚀 Fresher open to roles in AI Engineering, ML, Full-Stack & Data Science — ready to build and ship.
- 🤝 Always up for open-source collabs, hackathons & interesting ideas.
💻 Languages
🎨 Frontend
⚙️ Backend
🤖 AI / ML & Data Science
📊 Data Visualization
☁️ Hosting / SaaS
🛠️ Tools & Platforms
An end-to-end AI travel planner that builds fully personalized itineraries from uploaded travel documents. Uses a Hybrid RAG architecture with Llama 3.2 for reasoning and ChromaDB for semantic retrieval — turning unstructured PDFs into structured, day-by-day travel plans.
Tech Stack: Llama 3.2 ChromaDB RAG Streamlit Pandas PyMuPDF REST APIs
Ask anything from your documents — powered by Gemini API and a custom chunking strategy that improves retrieval precision over standard RAG. Supports multi-turn conversations with context retention, making dense documents actually queryable.
Tech Stack: Gemini API RAG ChromaDB LangChain Streamlit PyMuPDF Python
Content-based recommendation engine that suggests movies based on genre, cast, and plot similarity. Uses NLP techniques and cosine similarity to match user preferences with the most relevant titles.
Tech Stack: Scikit-learn Pandas NumPy NLP Cosine Similarity Streamlit Python
Data analytics project analysing Airbnb listing data to uncover host performance patterns, occupancy trends, and pricing dynamics. Delivers actionable insights on what makes a listing successful across different markets.
Tech Stack: Python Pandas NumPy Matplotlib Seaborn
- 🎖️ Deloitte Data Analytics Job Simulation
- 🎖️ Google AI-ML Virtual Internship
- 🎖️ IIT Bombay Java Training Certification
- 🎖️ Power BI by Microsoft
- 🎖️ Data Science for Python — NPTEL
- 📧 Email: vamsiandavarapu83096@gmail.com
- 💼 LinkedIn: https://www.linkedin.com/in/vamsiandavarapu
- 🌐 Portfolio: https://portfolio-.vercel.app/
- 🐙 GitHub: https://github.com/vamsiandavarapu
⭐ Turning Data into Insights and Ideas into Software Solutions