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This sample is part of the demo show in episode #2 for the Mechanics Series on Azure Cosmos DB for building intelligent apps. This sample demonstrates how to build a product recommendation system using the Alternating Least Squares algorithm with data from the .NET eShop sample.

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AzureCosmosDB/Retail-Product-Predictions

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Retail Product Predictions using ALS in pyspark

In this solution we will use Azure Cosmos DB for NoSQL (and Azure Cosmos DB for MongoDB) to demonstrate how you can build a purchasing prediction feature for an Ecommerce retail workload using collaborative filtering with the Alternative Least Squares model. Collaborative Filtering is the most implemented and mature recommendation system and the Alternative Least Squares (ALS) model is one of the most popular method in collaborative filtering.

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This sample is part of the demo show in episode #2 for the Mechanics Series on Azure Cosmos DB for building intelligent apps. This sample demonstrates how to build a product recommendation system using the Alternating Least Squares algorithm with data from the .NET eShop sample.

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