This document summarizes a student project report on developing a topic-based search engine for a website using machine learning. The project uses an instance-based learning algorithm (k-nearest neighbors) to classify HTML files into topics like artificial intelligence, programming languages, etc. It includes modules for training a classifier, crawling a website to index files into topics, and a search interface for users. The report describes implementing classes for preprocessing HTML, indexing, classification, and search functionality. Sample results show a keyword-based and topic-based search interface that returns relevant files.