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Big-Data

This project utilizes a dataset from Kaggle with 1.5 million rows and 13 columns with information on BeerAdvocate user reviews. I executed this project using Pyspark on AWS and created a recommender system using the Alternating Least Squares (ALS) algorithm from pyspark.ml to predict the ratings for beers which a user has not yet reviewed.

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