Flipboard

NOVEMBER 15, 2024

Metadata can play a very important role in using data assets to make data driven decisions. Generating metadata for your data assets is often a time-consuming and manual task. First, we explore the option of in-context learning, where the LLM generates the requested metadata without documentation.

Metadata 143

Metadata Generative AI LLM AI 143

AWS Machine Learning Blog

MAY 8, 2023

Because request_auth_aws_sigv4 uses Boto3 to retrieve credentials, we know that it can load credentials from the instance metadata when an IAM role is associated with an Amazon Elastic Compute Cloud (Amazon EC2) instance (for other ways to supply credentials to Boto3, see Credentials ).

Data Science 77

Data Science Machine Learning Python Data Scientist 77

AWS Machine Learning Blog

AUGUST 31, 2023

Model cards are intended to be a single source of truth for business and technical metadata about the model that can reliably be used for auditing and documentation purposes. They provide a fact sheet of the model that is important for model governance. For more information, refer to Configure the AWS CLI.

ML 110

ML Data Scientist Machine Learning Automation 110

AWS Machine Learning Blog

MAY 10, 2023

You can add metadata to the policy by attaching tags as key-value pairs, then choose Next: Review. His knowledge ranges from application architecture to big data, analytics, and machine learning. Choose Create policy. Choose Next: Tags. For more information about using tags in IAM, see Tagging IAM resources.

ML 85

ML Data Analysis Machine Learning Metadata 85

AWS Machine Learning Blog

AUGUST 31, 2023

Model cards are intended to be a single source of truth for business and technical metadata about the model that can reliably be used for auditing and documentation purposes. They provide a fact sheet of the model that is important for model governance. For more information, refer to Configure the AWS CLI.

ML 52

ML Data Scientist Machine Learning Automation 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Around this time, industry observers reported NVIDIA’s strategy pivoting from its traditional gaming and graphics focus to moving into scientific computing and data analytics. in 2012 is now widely referred to as ML’s “Cambrian Explosion.” The following table shows the metadata of three of the largest accelerated compute instances.

ML 95

ML Deep Learning Algorithm Large Language Models 95