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Analyze the interactions that users have with articles on the IBM Watson Studio platform, and make recommendations to them about new articles.

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Recommendations with IBM

Overview

An important part on IBM Watson Studio is the community; it's a collaborative ecosystem of curated datasets, articles, notebooks or other kinds of assets that are out there in the world of data science, machine learning and artificial intelligence. The data is the anonymized data of the interactions between all of the different kinds of articles, datasets etc available. The users interact with these assets on the platform.

The task is to build a personalized recommendation system for these assets in the community, and provide that presonalized recommendation experience with a web app.

Tasks

Exploratory Data Analysis

Rank Based Recommendations

User-User Based Collaborative Filtering

Content Based Recommendations

Matrix Factorization

Libraries

  • numpy
  • pandas
  • matplotlib

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Analyze the interactions that users have with articles on the IBM Watson Studio platform, and make recommendations to them about new articles.

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