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This repository is dedicated to the detection of faults in electric motors through machine learning techniques, specifically utilizing the K-Nearest Neighbors (KNN) algorithm. It contains datasets, Python scripts, and accompanying documentation necessary for implementing and understanding the fault detection process.
The project above is a browser extension that uses machine learning to train a model with a user's browsing history data and use it to make a decision on granting or blocking permissions for websites.
📌RAG-powered PDF chatbot that lets users chat with the contents of PDF documents using Retrieval-Augmented Generation (RAG) and LLMs. Built with a focus on document comprehension and conversational AI.
Built an intelligent assistant that analyzes real-estate data through natural language queries, generating insights and reports with dynamic SQL and Python code. Utilized LangChain for query handling, Google Maps API for location-based visualizations
VectorSearch with HNSW is a implementation of the Hierarchical Navigable Small World (HNSW) algorithm for efficient similarity search in high-dimensional vector spaces. This project demonstrates practical applications of approximate nearest neighbor search using the Fashion MNIST dataset, CIFAR-10 dataset as a case study.