Product Recommendation Engine
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Updated
Jan 14, 2019 - Python
Product Recommendation Engine
MVP for a recommendation engine based on Non-Negative Matrix Factorisation (NMF) [from scratch] #python #matrix-fatorization #product-ratings
An item-based recommender model that computes cosine similarity for each item pairs using the item factors matrix generated by Spark MLlib’s ALS algorithm and recommends top 5 items based on the selected item.
Robust product recommendations using topological data analysis. 4-week project completed during Insight Fellows Program, AI Silicon Valley 2020 B Cohort
GlancyAI is an LLM (like ChatGPT) that you can talk with, and it recommends products and helps you make your educated guess to buy a product.
This repository contains a Product Recommendation System built with Python, utilizing TF-IDF vectorization and cosine similarity to provide accurate recommendations based on product descriptions. It features an interactive Streamlit app for user-friendly input and real-time recommendations.
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