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

AWS Machine Learning Blog

This post details how Purina used Amazon Rekognition Custom Labels , AWS Step Functions , and other AWS Services to create an ML model that detects the pet breed from an uploaded image and then uses the prediction to auto-populate the pet attributes. Start the model version when training is complete.

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How LotteON built a personalized recommendation system using Amazon SageMaker and MLOps

AWS Machine Learning Blog

When training is complete (through the Lambda step), the deployed model is updated to the SageMaker endpoint. When the preprocessing batch was complete, the training/test data needed for training was partitioned based on runtime and stored in Amazon S3. This means keeping the same PyTorch and Python versions for training and inference.

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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning Blog

Create a KMS key in the dev account and give access to the prod account Complete the following steps to create a KMS key in the dev account: On the AWS KMS console, choose Customer managed keys in the navigation pane. Choose Create key. For Key type , select Symmetric. For Script Path , enter Jenkinsfile. Choose Save.

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Unleashing real-time insights: Monitoring SAP BTP cloud-native applications with IBM Instana

IBM Journey to AI blog

This solution extends observability to a wide range of roles, including DevOps, SRE, platform engineering, ITOps and development. You can find a complete list of supported technologies for IBM Instana on this page. Auto-discovery and dependency mapping : Automatically discovers and maps services and their interdependencies.

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Boost employee productivity with automated meeting summaries using Amazon Transcribe, Amazon SageMaker, and LLMs from Hugging Face

AWS Machine Learning Blog

The AWS partnership with Hugging Face allows a seamless integration through SageMaker with a set of Deep Learning Containers (DLCs) for training and inference, and Hugging Face estimators and predictors for the SageMaker Python SDK. Mateusz Zaremba is a DevOps Architect at AWS Professional Services. AWS CDK version 2.0

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15+ Artificial Intelligence AI Tools For Developers (2024)

Marktechpost

From completing entire lines of code and functions to writing comments and aiding in debugging and security checks, Copilot serves as an invaluable tool for developers. Mintlify Mintlify is a time-saving tool that auto-generates code documentation directly in your favorite code editor.

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15+ AI Tools For Developers (December 2023)

Marktechpost

From completing entire lines of code and functions to writing comments and aiding in debugging and security checks, Copilot serves as an invaluable tool for developers. Mintlify Mintlify is a time-saving tool that auto-generates code documentation directly in your favorite code editor.

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