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Recommendations with IBM

In this notebook, I am implementing recommendation methods on a real-world article dataset from the IBM Watson Studio platform. Please see the table of contents for the different sections covering different phases of the work / different types of recommendation logics:

Table of Contents

I. Exploratory Data Analysis
II. Rank Based Recommendations
III. User-User Based Collaborative Filtering
IV. Matrix Factorization

Please see IPython notebook for additional details.

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Recommender system for IBM Watson public articles

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