APIs Big data Consulting Training 
AWS Machine Learning
JUNE 30, 2022
In this post, we will continue to build on top of the previous solution to demonstrate how to build a private API Gateway via Amazon API Gateway as a proxy interface to generate and access Amazon SageMaker presigned URLs. The user invokes createStudioPresignedUrl API on API Gateway along with a token in the header.
AWS Machine Learning
AUGUST 3, 2023
Training ML algorithms for pose estimation requires a lot of expertise and custom training data. Therefore, we present two options: one that doesn’t require any ML expertise and uses Amazon Rekognition, and another that uses Amazon SageMaker to train and deploy a custom ML model.
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AWS Machine Learning
FEBRUARY 29, 2024
The Retrieve and RetrieveAndGenerate APIs allow your applications to directly query the index using a unified and standard syntax without having to learn separate APIs for each different vector database, reducing the need to write custom index queries against your vector store.
AWS Machine Learning
OCTOBER 27, 2022
In addition, features such as predictor retraining can reduce training time and cost by up to 50%. By separating popular from unpopular items and training predictors, we found that predictors can fit the dataset better and enhance model accuracy with different statistical distributions. Solution overview. Summary and next steps.
AWS Machine Learning
AUGUST 29, 2022
You can now use cross-account support for Amazon SageMaker Pipelines to share pipeline entities across AWS accounts and access shared pipelines directly through Amazon SageMaker API calls. The data scientist is now able to describe and monitor the test pipeline run status using SageMaker API calls from the dev account.
AWS Machine Learning
MARCH 23, 2023
Although this example shows how to perform this for inference operations, you can extend the solution to training and other ML steps. Endpoints are deployed with a couple clicks or lines of code using SageMaker, which simplifies the process for developers and ML experts to build and train ML and deep learning models in the cloud.
AWS Machine Learning
AUGUST 2, 2023
GenAI models are typically trained on vast amounts of data, which make them suitable for various tasks without additional training. Pre-training methods allow multi-modal applications to be easily trained using state-of-the-art language and image models. However, we can use CDE for a wider range of use cases.
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