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Amazon SageMaker

Facilitate data distribution through federated learning: A policy strategy for top digital executives.

Lead Data Scientist at T and T Consulting Services, Inc., Nitin Kumar, has written a guest blog post discussing the value and potential impact of federated learning in the healthcare field. In particular, it emphasizes the potential for applying the technology to quicker diagnoses and decision-making in heart stroke patients. Currently, strokes are the fifth leading…

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Using FedML on AWS for federated learning, along with Amazon SageMaker and Amazon EKS.

Many organizations are using machine learning (ML) to enhance their business decision-making processes through automation and by leveraging large distributed datasets. However, the sharing of raw, sensitive data in different locations brings about significant security and privacy risks. To combat these issues, federated learning (FL), a decentralized and collaborative ML training technique, is used. Traditional…

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Establish cross-account Amazon S3 accessibility for Amazon SageMaker notebooks functioning solely in VPC mode with the use of Amazon S3 Access Points.

Artificial intelligence (AI) and machine learning (ML) advancements are transforming the financial industry, enabling new use cases such as fraud detection and creditworthiness assessment. Access to large, disparate datasets, such as credit decision engines and customer transactions, is required for model development. The challenge is managing secure and compliant data access for data scientists working…

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Utilize Amazon SageMaker Canvas to identify irregularities in production data.

Cloud computing, including big data and machine learning (ML) tools like Amazon Athena and Amazon SageMaker, are becoming increasingly accessible and feasible to use for businesses in multiple industry sectors. This advancement is influencing a shift in resource efficiency by promoting data analytics and data-driven decision-making in operations, predictive maintenance, and planning. However, the rapid…

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Code Llama 70B can now be accessed via Amazon SageMaker JumpStart.

Meta has developed Code Llama, a state-of-the-art language model, aimed at generating code and assisting with coding tasks, and it is now available through Amazon's SageMaker JumpStart. Code Llama operates in Python, C++, Java, PHP, C#, TypeScript, and Bash, with the aim of boosting developers' productivity and streamlining software processes. The model explores three variations…

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How Axfood utilizes Amazon SageMaker to boost machine learning across the company.

Axfood, Sweden's second-largest food retailer, has succeeded in improving the efficiency and scalability of their AI and machine learning operations with the help of Amazon Web Services (AWS) experts using Amazon SageMaker. Despite having numerous data science teams with their own ways of working, the organization saw the need for a new Machine Learning Operations…

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Boost your AI group with Amazon SageMaker Studio: An extensive review of Deutsche Bahn’s AI platform overhaul

The growing influence of artificial intelligence (AI) in large organizations presents crucial challenges in managing AI platforms. These challenges include developing a scalable and operationally efficient platform that complies with organizational compliance and security standards. Amazon's SageMaker Studio offers a comprehensive set of capabilities for machine learning (ML) practitioners and data scientists. These capabilities include…

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