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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. Can you compare images?

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Host ML models on Amazon SageMaker using Triton: CV model with PyTorch backend

AWS Machine Learning Blog

Each model deployed with Triton requires a configuration file ( config.pbtxt ) that specifies model metadata, such as input and output tensors, model name, and platform. With a background in software engineering, she organically moved into an architecture role. Triton uses TorchScript for improved performance and flexibility.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning Blog

However, model governance functions in an organization are centralized and to perform those functions, teams need access to metadata about model lifecycle activities across those accounts for validation, approval, auditing, and monitoring to manage risk and compliance. region_name ram_client = boto3.client('ram')

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Top MLOps Tools Guide: Weights & Biases, Comet and More

Unite.AI

MLOps , or Machine Learning Operations, is a multidisciplinary field that combines the principles of ML, software engineering, and DevOps practices to streamline the deployment, monitoring, and maintenance of ML models in production environments. What is MLOps? We also save the trained model as an artifact using wandb.save().

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Managing Computer Vision Projects with Micha? Tadeusiak 

The MLOps Blog

What I mean is when data scientists are working hand in hand with software engineers or MLOps engineers, that would then take over or wrap up the solution. What’s your approach to different modalities of classification detection and segmentation? ” Michal: To be honest, we don’t use Auto ML too often.