Remove store landing 20-minute-managers
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Deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK

AWS Machine Learning Blog

You can access the pre-trained models, solution templates, and examples through the JumpStart landing page in Amazon SageMaker Studio. Fargate is a technology that you can use with Amazon ECS to run containers without having to manage servers or clusters or virtual machines. View the deployed resources on the AWS Management Console.

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Top AI Tools For Podcasting (2023)

Marktechpost

This AI tool enables all podcasters to effortlessly manage their audio files, improve their content, and increase their audience. Shownotes An AI-powered Shownotes automatically summarizes each podcast episode and generates a landing page with a transcript and captions file.

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Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

AWS Machine Learning Blog

For example, a model for a ride-sharing app can choose the best price for a ri­de from the airport, but only if it knows the number of ride requests received in the past 10 minutes and the number of passengers projected to land in the next 10 minutes. Try it out for yourself by visiting our GitHub repo.

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Integrate QnABot on AWS with ServiceNow

AWS Machine Learning Blog

According to Gartner Magic Quadrant 2023, ServiceNow is one of the leading IT Service Management (ITSM) providers on the market. ServiceNow’s Incident Management uses workflows to identify, track, and resolve high‑impact IT service incidents. You’re redirected to the landing page with the ServiceNow Developer program.

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Learnings From Building the ML Platform at Mailchimp

The MLOps Blog

She is currently the head of MLOps at FeatureForm , a virtual feature store. How did you manage to jump from a more analytical, scientific type of role to a more engineering one? Mikiko Bazeley: The boot camp didn’t put me in contact with hiring managers. There are three types of feature stores. It’s two things.

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Zero-shot text classification with Amazon SageMaker JumpStart

AWS Machine Learning Blog

You can access pre-trained models through the JumpStart landing page in Amazon SageMaker Studio. Complete the following steps: In SageMaker Studio, open the JumpStart landing page. This step takes a couple of minutes to complete. Refer to Open and use JumpStart for more details on how to navigate to SageMaker JumpStart.

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Automate the deployment of an Amazon Forecast time-series forecasting model

AWS Machine Learning Blog

Amazon Forecast is an ML-based time series forecasting service that includes algorithms that are based on over 20 years of forecasting experience used by Amazon.com , bringing the same technology used at Amazon to developers as a fully managed service, removing the need to manage resources.