Data Quality Metadata Software Development 
ODSC - Open Data Science
JULY 26, 2024
In particular, you’ll focus on tabular (or structured) synthetic data and the privacy-preserving benefits of working with synthetic data. You’ll even get hands-on with the open-source tool (DataLLM) and create tabular synthetic data yourselves. Gen AI in Software Development. What should you be looking for?
The MLOps Blog
APRIL 17, 2023
Building a tool for managing experiments can help your data scientists; 1 Keep track of experiments across different projects, 2 Save experiment-related metadata, 3 Reproduce and compare results over time, 4 Share results with teammates, 5 Or push experiment outputs to downstream systems.
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AWS Machine Learning Blog
NOVEMBER 15, 2023
Therefore, when the Principal team started tackling this project, they knew that ensuring the highest standard of data security such as regulatory compliance, data privacy, and data quality would be a non-negotiable, key requirement. He has 20 years of enterprise software development experience.
AWS Machine Learning Blog
NOVEMBER 14, 2024
Model governance involves overseeing the development, deployment, and maintenance of ML models to help ensure that they meet business objectives and are accurate, fair, and compliant with regulations. It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices.
AWS Machine Learning Blog
FEBRUARY 21, 2023
With this option, you are testing the new model and minimizing the risks of a low-performing model, and you can compare both models’ performance with the same data. SageMaker deployment guardrails Guardrails are an essential part of software development.
AWS Machine Learning Blog
NOVEMBER 7, 2024
The AWS managed offering ( SageMaker Ground Truth Plus ) designs and customizes an end-to-end workflow and provides a skilled AWS managed team that is trained on specific tasks and meets your data quality, security, and compliance requirements. The following example describes usage and cost per model per tenant in Athena.
The MLOps Blog
MARCH 15, 2023
Cost and resource requirements There are several cost-related constraints we had to consider when we ventured into the ML model deployment journey Data storage costs: Storing the data used to train and test the model, as well as any new data used for prediction, can add to the cost of deployment. S3 buckets.
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