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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning Blog

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems.

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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

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Can you see the complete model lineage with data/models/experiments used downstream? Amazon SageMaker Ground Truth SageMaker Ground Truth is a fully managed data labeling service designed to help you efficiently label and annotate your training data with high-quality annotations. Can you render audio/video?