Rahul Singh

End-to-end IPL analytics and machine learning project with data cleaning, EDA, feature engineering, Gradient Boosting model, and Streamlit app to predict 50+ scores. Built using Python, Pandas, Scikit-learn, Matplotlib, and Seaborn.

Production-style AI customer support agent built with LangGraph, RAG, Gemini, FastAPI, policy resolution, safety guardrails, and observability.

My NeetCode.io problem submissions

A collection of LangGraph, LangChain, and LangSmith tutorials covering AI workflows, RAG, chatbots, memory, tools, persistence, PostgreSQL, Docker, and Streamlit.

A collection of Jupyter notebooks demonstrating LangChain and RAG concepts, from LLM fundamentals to agents, tools, retrievers, and vector databases.

End-to-end Machine Learning project to predict customer churn using Scikit-learn pipelines, feature engineering, model tuning, and a Streamlit web app.

A modern portfolio website showcasing my projects, skills, and experience as an AI & Data Science student .

A full-stack Task Manager Dashboard built with Java 11 (Sun HttpServer) and Angular 15. Supports Basic Authentication, CRUD task management, filtering, pagination, and in-memory storage using Concurrent HashMap. Developed as part of a full-stack assessment.