Machine-learning-at-Scale

Code and demonstrate a prototype of a recommender system utilizing the 25M MovieLens dataset.

The implementation utilizes a matrix factorization approach to leverage the 25 million ratings available in the dataset.

The technical report showcases the recommendation engine prototype and outlines the step-by-step process employed in its development.

Name		Name	Last commit message	Last commit date
ML at scale report & VI approach.pdf		ML at scale report & VI approach.pdf
README.md		README.md
Recommender prototype.ipynb		Recommender prototype.ipynb
Technical_report.pdf		Technical_report.pdf
Variational_Bayes_Approach.ipynb		Variational_Bayes_Approach.ipynb

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