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User article recommendation engine using Singular Value Decomposition (SVD) algorithm to detect latent features and suggest new articles to users.

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jhmarlow/user-article-recommendation-engine

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User Article Recommendation with IBM Watson

Overview

This project contains the code developed as part of reccommending articles to users based on a Singular Value Decomposition (SVD) reccomendation engine. This ML model is used to identify latent features and articles to recommend users new articles based on the behaviour of similar users.

Prerequisites

  • Python
  • Jupyter
  • Packages (see requirements.txt)

Quickstart

View notebooks/reccommendations_with_ibm.ipynb.

Project Structure

  • notebooks - contains notebooks used to develop and test reccommendation engine
  • reccommendation-engine-deployment - contains code made available by udacity for deployment.

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User article recommendation engine using Singular Value Decomposition (SVD) algorithm to detect latent features and suggest new articles to users.

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