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Prompt-Based Automated Data Labeling and Annotation

Towards AI

Nothing in the world motivates a team of ML engineers and scientists to spend the required amount of time in data annotation and labeling. Now if you see, it's a complete workflow optimization challenge centered around the ability to execute data-related operations 10x faster. It's a new need now.

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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning Blog

The AWS portfolio of ML services includes a robust set of services that you can use to accelerate the development, training, and deployment of machine learning applications. The suite of services can be used to support the complete model lifecycle including monitoring and retraining ML models.

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MLOps with Comet - A Machine Learning Platform

Heartbeat

Comet Comet is a machine learning platform built to help data scientists and ML engineers track, compare, and optimize machine learning experiments. Image by Author If you want to end the experiment, you can use the end method of the Experiment object to mark the experiment as complete. #

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How VMware built an MLOps pipeline from scratch using GitLab, Amazon MWAA, and Amazon SageMaker

Flipboard

We orchestrate our ML training and deployment pipelines using Amazon Managed Workflows for Apache Airflow (Amazon MWAA), which enables us to focus more on programmatically authoring workflows and pipelines without having to worry about auto scaling or infrastructure maintenance.

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The Sequence Chat: Hugging Face's Leandro von Werra on StarCoder and Code Generating LLMs

TheSequence

data or auto-generated files). cell outputs) for code completion in Jupyter notebooks (see this Jupyter plugin ). Were there any research breakthroughs in StarCoder, or would you say it was more of a crafty ML engineering effort? In addition we labelled a PII dataset for code to train a PII detector.

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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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Prioritizing employee well-being: An innovative approach with generative AI and Amazon SageMaker Canvas

AWS Machine Learning Blog

In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing. Complete the following steps: Choose Prepare and analyze data. Complete the following steps: Choose Run Data quality and insights report. Choose Create. Choose Export.