AWS Machine Learning

JANUARY 5, 2024

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.

Management 109

Management APIs Engineering Government 109

AWS Machine Learning

DECEMBER 1, 2022

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 74

APIs Analytics Engineering Technology 74

AWS Machine Learning

SEPTEMBER 6, 2023

It’s powered by large language models (LLMs) that are pre-trained on vast amounts of data and commonly referred to as foundation models (FMs). These SageMaker endpoints are consumed in the Amplify React application through Amazon API Gateway and AWS Lambda functions. This dataset is a large corpus of legal and administrative data.

Enterprise 94

Enterprise APIs Real estate Construction 94

AWS Machine Learning

NOVEMBER 1, 2022

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.

Engineering 91

Engineering APIs Accountability industry solution 91

AWS Machine Learning

FEBRUARY 13, 2023

With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to marketing), the primary focus shifts to efficiency when building and training models at scale. Navigate to the AWS Cloud9 console.

Scripts 74

Scripts Best practices Transportation Construction 74

AWS Machine Learning

JUNE 14, 2023

Amazon SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. You then can directly deploy the model to production with just one click or iterate on the recommended solutions to further improve the model quality.

Best practices 77

Best practices Scripts Engineering Education 77