Remove Accountability Remove Analysis Remove APIs Remove Big data
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Reduce food waste to improve sustainability and financial results in retail with Amazon Forecast

AWS Machine Learning

We can then call a Forecast API to create a dataset group and import data from the processed S3 bucket. We use the AutoPredictor API, which is also accessible through the Forecast console. For customized evaluation and analysis, you can also export the forecasted values to evaluate predictor quality metrics.

APIs 97
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Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

AWS Machine Learning

Before you get started, refer to Part 1 for a high-level overview of the insurance use case with IDP and details about the data capture and classification stages. In Part 1, we saw how to use Amazon Textract APIs to extract information like forms and tables from documents, and how to analyze invoices and identity documents.

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­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account. SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Table formats provide a way to abstract data files as a table. You can also use the FeatureGroup().put_record

Scripts 73
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Intelligent document processing with AWS AI services: Part 2

AWS Machine Learning

More specifically, we need to identify the customer’s savings and checking account numbers in the bank statement. The entities in this file are going to be specific to our business needs (savings and checking account numbers). We can extract these key business terms using Amazon Comprehend custom entity recognition. to Amazon Textract.

Banking 74
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How Patsnap used GPT-2 inference on Amazon SageMaker with low latency and cost

AWS Machine Learning

Patsnap provides a global one-stop platform for patent search, analysis, and management. They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. implement the model and the inference API. get_caller_identity()['Account'] region = boto3.Session().region_name

APIs 66
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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

In addition to awareness, your teams should take action to account for generative AI in governance, assurance, and compliance validation practices. You should begin by extending your existing security, assurance, compliance, and development programs to account for generative AI.

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Build and train computer vision models to detect car positions in images using Amazon SageMaker and Amazon Rekognition

AWS Machine Learning

Finally, we show how you can integrate this car pose detection solution into your existing web application using services like Amazon API Gateway and AWS Amplify. For each option, we host an AWS Lambda function behind an API Gateway that is exposed to our mock application. Aamna Najmi is a Data Scientist with AWS Professional Services.

APIs 63