AWS Machine Learning Blog Amazon SageMaker is a fully managed machine learning (ML) platform that offers a comprehensive set of services that serve end-to-end ML workloads. As recommended by AWS as a best practice, customers have used separate accounts to simplify policy management for users and isolate resources by workloads and account. However, when more […]Continue reading
AWS Machine Learning Blog Amazon SageMaker Canvas is a visual interface that enables business analysts to generate accurate machine learning (ML) predictions on their own, without requiring any ML experience or having to write a single line of code. SageMaker Canvas’s intuitive user interface lets business analysts browse and access disparate data sources in the […]Continue reading
AWS Machine Learning Blog Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines search for your websites and applications so your employees and customers can easily find the content they are looking for, even when it’s scattered across multiple locations and content repositories within your organization. Amazon Kendra supports […]Continue reading
AWS Machine Learning Blog Amazon SageMaker Model Cards enable you to standardize how models are documented, thereby achieving visibility into the lifecycle of a model, from designing, building, training, and evaluation. Model cards are intended to be a single source of truth for business and technical metadata about the model that can reliably be used […]Continue reading
AWS Machine Learning Blog Amazon Lex is a service that allows you to quickly and easily build conversational bots (“chatbots”), virtual agents, and interactive voice response (IVR) systems for applications such as Amazon Connect. Artificial intelligence (AI) and machine learning (ML) have been a focus for Amazon for over 20 years, and many of the […]Continue reading
AWS Machine Learning Blog Amazon SageMaker is an end-to-end machine learning (ML) platform with wide-ranging features to ingest, transform, and measure bias in data, and train, deploy, and manage models in production with best-in-class compute and services such as Amazon SageMaker Data Wrangler, Amazon SageMaker Studio, Amazon SageMaker Canvas, Amazon SageMaker Model Registry, Amazon SageMaker […]Continue reading
AWS Machine Learning Blog Amazon Polly is a service that turns text into lifelike speech. It enables the development of a whole class of applications that can convert text into speech in multiple languages. This service can be used by chatbots, audio books, and other text-to-speech applications in conjunction with other AWS AI or machine […]Continue reading
AWS Machine Learning Blog Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. With SageMaker JumpStart, you can discover and deploy publicly available and proprietary foundation models to dedicated Amazon SageMaker instances for your generative AI applications. SageMaker JumpStart allows you to deploy foundation models from a […]Continue reading
AWS Machine Learning Blog Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code. SageMaker Data Wrangler […]Continue reading
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