Favorite In this post, we walk you through two sampling techniques in Amazon SageMaker Data Wrangler so you can quickly create processing workflows for your data. We cover both random sampling and stratified sampling techniques to help you sample your data based on your specific requirements. Data Wrangler reduces the

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Shared by AWS Machine Learning April 27, 2022

Favorite In this post, we demonstrate Kubeflow on AWS (an AWS-specific distribution of Kubeflow) and the value it adds over open-source Kubeflow through the integration of highly optimized, cloud-native, enterprise-ready AWS services. Kubeflow is the open-source machine learning (ML) platform dedicated to making deployments of ML workflows on Kubernetes simple,

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Shared by AWS Machine Learning April 27, 2022

Favorite Nordic Aviation Capital (NAC) is the industry’s leading regional aircraft lessor, serving almost 70 airlines in approximately 45 countries worldwide. In 2021, NAC turned to AWS to help it use artificial intelligence (AI) to further improve its leasing operations and reduce its reliance on manual labor. With Amazon Rekognition

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Shared by AWS Machine Learning April 26, 2022

Favorite The last few years have seen rapid growth in the field of natural language processing (NLP) using transformer deep learning architectures. With its Transformers open-source library and machine learning (ML) platform, Hugging Face makes transfer learning and the latest transformer models accessible to the global AI community. This can

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Shared by AWS Machine Learning April 26, 2022

Favorite Amazon SageMaker Data Wrangler is a new capability of Amazon SageMaker that helps data scientists and data engineers quickly and easily prepare data for machine learning (ML) applications using a visual interface. It contains over 300 built-in data transformations so you can quickly normalize, transform, and combine features without

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Shared by AWS Machine Learning April 26, 2022

Favorite This is the first post of a four-part series detailing how NatWest Group, a major financial services institution, partnered with AWS to build a scalable, secure, and sustainable machine learning operations (MLOps) platform. This initial post provides an overview of the AWS and NatWest Group joint team implemented Amazon

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Shared by AWS Machine Learning April 26, 2022

Favorite This is the second post of a four-part series detailing how NatWest Group, a major financial services institution, partnered with AWS Professional Services to build a new machine learning operations (MLOps) platform. In this post, we share how the NatWest Group utilized AWS to enable the self-service deployment of

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Shared by AWS Machine Learning April 26, 2022

Favorite This is the third post of a four-part series detailing how NatWest Group, a major financial services institution, partnered with AWS Professional Services to build a new machine learning operations (MLOps) platform. This post is intended for data scientists, MLOps engineers, and data engineers who are interested in building

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Shared by AWS Machine Learning April 26, 2022

Favorite The adoption of AWS cloud technology at NatWest Group means moving our machine learning (ML) workloads to a more robust and scalable solution, while reducing our time-to-live to deliver the best products and services for our customers. In this cloud adoption journey, we selected the Customer Lifetime Value (CLV)

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Shared by AWS Machine Learning April 26, 2022

Favorite AWS CodeArtifact allows developers to connect internal code repositories to upstream code repositories like Pypi, Maven, or NPM. AWS CodeArtifact is a powerful addition to CI/CD workflows on AWS, but it is similarly effective for code-bases hosted on a Jupyter notebook. This is a common development paradigm for Machine

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Shared by AWS Machine Learning April 23, 2022