Recommendation using embeddings and nearest neighbor search

# Recommendation using embeddings and nearest neighbor search Recommendations are widespread across the web. - 'Bought that item? Try these similar items.' - 'Enjoy that book? Try these similar titles.' - 'Not the help page you were looking for? Try these similar pages.' This notebook demonstrates how to use embeddings to find similar items to recommend. In particular, we use [AG's corpus of news articles](http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html) as our dataset. Our model will answer the question: given an article, what other articles are most similar to it?