LangChain-Powered RAG for Intelligent Web Content QA

• Built a Retrieval-Augmented Generation (RAG) pipeline combining LangChain with FAISS for semantic search across large web corpora. • Leveraged HuggingFace embeddings to create dense vector representations of documents, facilitating accurate retrieval of top-k chunks. • Integrated a Groq-hosted LLM

AI-Powered Feedback Insight Engine (No-Code with N8n + LLMs)

Designed and deployed a fully automated pipeline to extract actionable insights from user feedback using no-code tools and LLM-driven sentiment & topic analysis.

Click Throw Rate Predictor in Gmail

The Click-Through Rate (CTR) Predictor project aims to forecast the likelihood of users clicking on email advertisements within the Gmail platform. By leveraging machine learning algorithms and user engagement data, the system provides advertisers with valuable insights to optimize their email marke

Boston House Price Predictor

The Boston House Price Predictor project focuses on predicting the prices of houses in the Boston area using machine learning algorithms. By analyzing historical housing data and relevant features, the system assists prospective homebuyers, sellers, and real estate professionals in estimating proper

Flight Fare Predictor India

The Flight Fare Prediction project focuses on predicting airfare prices for domestic flights in India. Leveraging machine learning algorithms and historical flight data, the system aims to provide accurate fare estimates to travelers, helping them plan their journeys more efficiently.

Used Cars Price Predictor

The Used Car Price Predictor project aims to assist car buyers and sellers in estimating the fair market value of used cars. Leveraging machine learning algorithms and real-world data from Cars24, the system predicts the price of a used car based on various factors such as make, model,Etc...