AWS Machine Learning Blog

APRIL 19, 2024

We perform a k-nearest neighbor (k-NN) search to retrieve the most relevant embeddings matching the user query. As per the AI/ML flywheel, what do the AWS AI/ML services provide? Based on the summary, the AWS AI/ML services provide a range of capabilities that fuel an AI/ML flywheel.

AWS 125

AWS ML ML Database 125

AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. In this post, we deep dive into the technical details of this ML model.

ML 89

ML ML Machine Learning Machine Learning 89

AWS Machine Learning Blog

DECEMBER 6, 2023

Another driver behind RAG’s popularity is its ease of implementation and the existence of mature vector search solutions, such as those offered by Amazon Kendra (see Amazon Kendra launches Retrieval API ) and Amazon OpenSearch Service (see k-Nearest Neighbor (k-NN) search in Amazon OpenSearch Service ), among others.

SQL 126

SQL AWS Analytics Analytics 126

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. First, “Selection via Proxy,” which appeared in ICLR 2020. I’m super excited to chat with you all today.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. First, “Selection via Proxy,” which appeared in ICLR 2020. I’m super excited to chat with you all today.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

I’m Cody Coleman and I’m really excited to share my research on how careful data selection can make ML development faster, cheaper, and better by focusing on quality rather than quantity. First, “Selection via Proxy,” which appeared in ICLR 2020. I’m super excited to chat with you all today.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52