Remove AWS Remove Clustering Remove Deep Learning Remove K-nearest Neighbors
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Implement unified text and image search with a CLIP model using Amazon SageMaker and Amazon OpenSearch Service

AWS Machine Learning Blog

k-NN index query – This is the inference phase of the application. In this phase, you submit a text search query or image search query through the deep learning model (CLIP) to encode as embeddings. Then, you use those embeddings to query the reference k-NN index stored in OpenSearch Service. bin/bash MODEL_NAME=RN50.pt

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Power recommendations and search using an IMDb knowledge graph – Part 3

AWS Machine Learning Blog

Many AWS media and entertainment customers license IMDb data through AWS Data Exchange to improve content discovery and increase customer engagement and retention. We downloaded the data from AWS Data Exchange and processed it in AWS Glue to generate KG files. Background. Solution overview. Prerequisites.

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Identifying defense coverage schemes in NFL’s Next Gen Stats

AWS Machine Learning Blog

We design a K-Nearest Neighbors (KNN) classifier to automatically identify these plays and send them for expert review. As an example, in the following figure, we separate Cover 3 Zone (green cluster on the left) and Cover 1 Man (blue cluster in the middle). Outside of work, he enjoys soccer and video games.

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