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GraphStorm 0.3: Scalable, multi-task learning on graphs with user-friendly APIs

AWS Machine Learning

adds new APIs to customize GraphStorm pipelines: you now only need 12 lines of code to implement a custom node classification training loop. Based on customer feedback for the experimental APIs we released in GraphStorm 0.2, introduces refactored graph ML pipeline APIs. Specifically, GraphStorm 0.3 In addition, GraphStorm 0.3

APIs 117
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Generate training data and cost-effectively train categorical models with Amazon Bedrock

AWS Machine Learning

These include metrics such as ROUGE or cosine similarity for text similarity, and specific benchmarks for assessing toxicity (Detoxify), prompt stereotyping (cross-entropy loss), or factual knowledge (HELM, LAMA). We suggest consulting LLM prompt engineering documentation such as Anthropic prompt engineering for experiments.

Education 110
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Optimize pet profiles for Purina’s Petfinder application using Amazon Rekognition Custom Labels and AWS Step Functions

AWS Machine Learning

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Purina’s solution is deployed as an API Gateway HTTP endpoint, which routes the requests to obtain pet attributes.

APIs 127
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Cepsa Química improves the efficiency and accuracy of product stewardship using Amazon Bedrock

AWS Machine Learning

We partnered with Keepler , a cloud-centered data services consulting company specialized in the design, construction, deployment, and operation of advanced public cloud analytics custom-made solutions for large organizations, in the creation of the first generative AI solution for one of our corporate teams.

APIs 126
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Evaluation of generative AI techniques for clinical report summarization

AWS Machine Learning

This is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API. It’s serverless, so you don’t have to manage any infrastructure.

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Important KPIs for Measuring Customer Satisfaction

Fonolo

It’s important for all departments to have benchmarks for success that can be easily measured and tracked. Call center and customer service teams have a variety of KPIs to choose from, but as each company and support department is different, their benchmarks will vary. He leads product management for Nexmo, the Vonage API Platform.

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Generating fashion product descriptions by fine-tuning a vision-language model with SageMaker and Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Scripts 135