AWS Machine Learning Blog
DECEMBER 13, 2023
To deliver value, they must integrate into existing production systems and infrastructure, which necessitates considering the entire ML lifecycle during design and development. ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle.
AWS Machine Learning Blog
SEPTEMBER 20, 2023
This approach is beneficial if you use AWS services for ML for its most comprehensive set of features, yet you need to run your model in another cloud provider in one of the situations we’ve discussed. Organizations can also use AWS Trainium and AWS Inferentia for better price-performance for running ML training jobs or inference.
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AWS Machine Learning Blog
SEPTEMBER 1, 2023
After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. Security SMEs review the architecture based on business security policies and needs.
AWS Machine Learning Blog
NOVEMBER 9, 2023
Automated retraining mechanism – The training pipeline built with SageMaker Pipelines is triggered whenever a data drift is detected in the inference pipeline. Download and save the publicly available UCI Mammography Mass dataset to the S3 bucket you created earlier in the dev account. data/ mammo-train-dataset-part2.csv csv dataset.
AWS Machine Learning Blog
APRIL 29, 2024
Metaflow overview Metaflow was originally developed at Netflix to enable data scientists and ML engineers to build ML/AI systems quickly and deploy them on production-grade infrastructure. Deployment To deploy a Metaflow stack using AWS CloudFormation , complete the following steps: Download the CloudFormation template.
The MLOps Blog
MARCH 15, 2023
Automation : Automating as many tasks to reduce human error and increase efficiency. Collaboration : Ensuring that all teams involved in the project, including data scientists, engineers, and operations teams, are working together effectively. But we chose not to go with the same in our deployment due to a couple of reasons.
The MLOps Blog
JANUARY 26, 2024
We’ll see how this architecture applies to different classes of ML systems, discuss MLOps and testing aspects, and look at some example implementations. Understanding machine learning pipelines Machine learning (ML) pipelines are a key component of ML systems. But what is an ML pipeline?
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