Showing results for electronics Vector Vector Vector Product
GitHub Repo
https://github.com/SanthoshDhandapani/FindIt
SanthoshDhandapani/FindIt
FindIt is an AI-powered e-commerce search engine that understands what you mean, not just what you type. Built on CrewAI agents, Pinecone vector search, and hybrid semantic-keyword retrieval — it delivers relevancy-ranked product results across Electronics, Shoes, and Stationery.
GitHub Repo
https://github.com/mtsokanlawon/product_categorizer_bf
mtsokanlawon/product_categorizer_bf
E-commerce Product Categorization: A machine learning project that classifies product descriptions into categories such as Books, Electronics, Clothing, and Household. Using TF-IDF vectorization for text representation and a Logistic Regression baseline model, this project demonstrates an end-to-end pipeline for text preprocessing, training & eval
GitHub Repo
https://github.com/madesh6554/Smart-Electronics-Recommendation-System
madesh6554/Smart-Electronics-Recommendation-System
The Smart Product Recommendation System is a web-based application built with Streamlit and Python to help users discover products based on their preferences. It uses Natural Language Processing (NLP) techniques like TF-IDF vectorization and cosine similarity to recommend products with similar characteristics.
GitHub Repo
https://github.com/hoangsonww/MERN-Stack-Ecommerce-App
hoangsonww/MERN-Stack-Ecommerce-App
🛒 Welcome to Fusion Electronics - a sample full-stack, lightweight, and modern online e-commerce application, built with the MERN (MongoDB, Express, React, Node.js) stack! Also features a product recommendation service using vector search, FAISS, and the Weaviate/Pinecone vector DB!
GitHub Repo
https://github.com/Qurban1998/RAG-analysis
Qurban1998/RAG-analysis
AI-driven analytics for a consumer electronics e-commerce firm with 2.3% conversions. Combines ChromaDB vector search (MiniLM embeddings) on reviews, product descriptions, and market reports, cosine similarity gap analysis (45% below 0.50), and RAG synthesis of strategic insights.
GitHub Repo
https://github.com/Sivaramasaran2773/E-Commerce-Product-Categorization-using-NLP-and-Machine-Learning.
Sivaramasaran2773/E-Commerce-Product-Categorization-using-NLP-and-Machine-Learning.
This repository classifies e-commerce products using NLP and ML. The process involves text normalization, vectorization (TF-IDF, Bag of Words, word2Vec, fastText, BERT), and classification (SVM, KNN, Random Forest, LightGBM, XGBoost). It handles four categories: Electronics, Household, Books, and Clothing & Accessories.
GitHub Repo
https://github.com/Shrijul-Venkatesh/nexus-electronics
Shrijul-Venkatesh/nexus-electronics
A full-stack MERN e-commerce platform featuring product browsing, cart and checkout flows, authentication, and AI-powered product recommendations using vector search.
GitHub Repo
https://github.com/Farasat123/E-Commerce-Website-Advanced-
Farasat123/E-Commerce-Website-Advanced-
Welcome to Fusion Electronics - a sample full-stack, lightweight, and modern online e-commerce application, built with the MERN (MongoDB, Express, React, Node.js) stack! Also features a product recommendation service using vector search, FAISS, and the Weaviate/Pinecone vector DB!
GitHub Repo
https://github.com/Akshayaa-bk/E-Commerce-Product-Categorization-using-NLP-and-Machine-Learning.
Akshayaa-bk/E-Commerce-Product-Categorization-using-NLP-and-Machine-Learning.
This repository classifies e-commerce products using NLP and ML. The process involves text normalization, vectorization (TF-IDF, Bag of Words, word2Vec, fastText, BERT), and classification (SVM, KNN, Random Forest, LightGBM, XGBoost). It handles four categories: Electronics, Household, Books, and Clothing & Accessories.
GitHub Repo
https://github.com/shinycrow401/Fusion-Electronics---ECommerce