Semantic text search using embeddings

## Semantic text search using embeddings We can search through all our reviews semantically in a very efficient manner and at very low cost, by embedding our search query, and then finding the most similar reviews. The dataset is created in the [Get_embeddings_from_dataset Notebook](Get_embeddings_from_dataset.ipynb). Here we compare the cosine similarity of the embeddings of the query and the documents, and show top_n best matches. We can search through these reviews easily. To speed up computation, we can use a special algorithm, aimed at faster search through embeddings.