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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems.

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Amazon Bedrock Custom Model Import now generally available

AWS Machine Learning

This feature empowers customers to import and use their customized models alongside existing foundation models (FMs) through a single, unified API. Having a unified developer experience when accessing custom models or base models through Amazon Bedrock’s API. The training data must be formatted in a JSON Lines (.jsonl)

APIs 139
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Build an agronomic data platform with Amazon SageMaker geospatial capabilities

AWS Machine Learning

Data-driven decisions fueled by near-real-time insights can enable farmers to close the gap on increased food demand. However, scouting each field on a frequent basis for large fields and farms is not feasible, and successful risk mitigation requires an integrated agronomic data platform that can bring insights at scale.

APIs 86
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Automate cloud security vulnerability assessment and alerting using Amazon Bedrock

AWS Machine Learning

GuardDuty combines machine learning (ML), anomaly detection, and malicious file discovery, using both AWS and industry-leading third-party sources, to help protect AWS accounts, workloads, and data. Generative AI can make predictions about future security threats or attacks by analyzing historical security data and trends.

APIs 72
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Enhance call center efficiency using batch inference for transcript summarization with Amazon Bedrock

AWS Machine Learning

This new feature enables organizations to process large volumes of data when interacting with foundation models (FMs), addressing a critical need in various industries, including call center operations. As the volume of call data grows, traditional analysis methods struggle to keep pace, creating a demand for a scalable solution.

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Automated exploratory data analysis and model operationalization framework with a human in the loop

AWS Machine Learning

Identifying, collecting, and transforming data is the foundation for machine learning (ML). According to a Forbes survey , there is widespread consensus among ML practitioners that data preparation accounts for approximately 80% of the time spent in developing a viable ML model. Overview of solution.

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Accenture creates a regulatory document authoring solution using AWS generative AI services

AWS Machine Learning

Accenture built a regulatory document authoring solution using automated generative AI that enables researchers and testers to produce CTDs efficiently. By extracting key data from testing reports, the system uses Amazon SageMaker JumpStart and other AWS AI services to generate CTDs in the proper format.