To properly provide recommended results to the user, we first need to train it on a large database. To do this, we'll use the Amazon India Product Listing Dataset. Before training, we'll need to transform the UCSD Amazon database into a matrix which has the same parameters as our data since the Amazon database will have more detail in its reviews and metadata, and we won't need to use all of those details.
Problem You're Trying to Solve
A user needs to view curated recommendations on their marketplace as a requirement in the specification. By training the recommender, we will be able to make predictions about the content a user wants to see.
Feature Description
To properly provide recommended results to the user, we first need to train it on a large database. To do this, we'll use the Amazon India Product Listing Dataset. Before training, we'll need to transform the UCSD Amazon database into a matrix which has the same parameters as our data since the Amazon database will have more detail in its reviews and metadata, and we won't need to use all of those details.
Problem You're Trying to Solve
A user needs to view curated recommendations on their marketplace as a requirement in the specification. By training the recommender, we will be able to make predictions about the content a user wants to see.
Related External Resources
https://cseweb.ucsd.edu/~jmcauley/datasets.html#amazon_reviews