Categoría: Artificial Intelligence*

Auto Added by WPeMatico

New – Ready-to-use Models and Support for Custom Text and Image Classification Models in Amazon SageMaker Canvas

Publicada el por Stack Over Cloud

Today AWS announces new features in Amazon SageMaker Canvas that help business analysts generate insights from thousands of documents, images, and lines of text in minutes with machine learning (ML). Starting today, you can access ready-to-use models and create custom text and image classification models alongside previously supported custom models for tabular data, all without Read more about New – Ready-to-use Models and Support for Custom Text and Image Classification Models in Amazon SageMaker Canvas[…]

Amazon Chime SDK Call Analytics: Real-Time Voice Tone Analysis and Speaker Search

Publicada el por Stack Over Cloud

Today, I am pleased to announce the availability of Amazon Chime SDK call analytics, a new set of capabilities that helps make it easier and cost effective to record and generate insights on real-time audio calls: transcription, voice tone analysis, and speaker search. We’ve also improved the Amazon Chime SDK section of the AWS Management Read more about Amazon Chime SDK Call Analytics: Real-Time Voice Tone Analysis and Speaker Search[…]

AWS Week in Review – March 20, 2023

Publicada el por Stack Over Cloud

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS! A new week starts, and Spring is almost here! If you’re curious about AWS news from the previous seven days, I got you covered. Last Week’s Launches Here are the Read more about AWS Week in Review – March 20, 2023[…]

AWS Week in Review – February 27, 2023

Publicada el por Stack Over Cloud

A couple days ago, I had the honor of doing a live stream on generative AI, discussing recent innovations and concepts behind the current generation of large language and vision models and how we got there. In today’s roundup of news and announcements, I will share some additional information—including an expanded partnership to make generative Read more about AWS Week in Review – February 27, 2023[…]

AWS Week in Review – January 16, 2023

Publicada el por Stack Over Cloud

Today, we celebrate Martin Luther King Jr. Day in the US to honor the late civil rights leader’s life, legacy, and achievements. In this article, Amazon employees share what MLK Day means to them and how diversity makes us stronger. Coming back to our AWS Week in Review—it’s been a busy week! Last Week’s Launches Read more about AWS Week in Review – January 16, 2023[…]

New – Bring ML Models Built Anywhere into Amazon SageMaker Canvas and Generate Predictions

Publicada el por Stack Over Cloud

Amazon SageMaker Canvas provides business analysts with a visual interface to solve business problems using machine learning (ML) without writing a single line of code. Since we introduced SageMaker Canvas in 2021, many users have asked us for an enhanced, seamless collaboration experience that enables data scientists to share trained models with their business analysts Read more about New – Bring ML Models Built Anywhere into Amazon SageMaker Canvas and Generate Predictions[…]

New – Process PDFs, Word Documents, and Images with Amazon Comprehend for IDP

Publicada el por Stack Over Cloud

Today we are announcing a new Amazon Comprehend feature for intelligent document processing (IDP). This feature allows you to classify and extract entities from PDF documents, Microsoft Word files, and images directly from Amazon Comprehend without you needing to extract the text first. Many customers need to process documents that have a semi-structured format, like Read more about New – Process PDFs, Word Documents, and Images with Amazon Comprehend for IDP[…]

New for Amazon SageMaker – Perform Shadow Tests to Compare Inference Performance Between ML Model Variants

Publicada el por Stack Over Cloud

As you move your machine learning (ML) workloads into production, you need to continuously monitor your deployed models and iterate when you observe a deviation in your model performance. When you build a new model, you typically start validating the model offline using historical inference request data. But this data sometimes fails to account for Read more about New for Amazon SageMaker – Perform Shadow Tests to Compare Inference Performance Between ML Model Variants[…]

Next Generation SageMaker Notebooks – Now with Built-in Data Preparation, Real-Time Collaboration, and Notebook Automation

Publicada el por Stack Over Cloud

In 2019, we introduced Amazon SageMaker Studio, the first fully integrated development environment (IDE) for data science and machine learning (ML). SageMaker Studio gives you access to fully managed Jupyter Notebooks that integrate with purpose-built tools to perform all ML steps, from preparing data to training and debugging models, tracking experiments, deploying and monitoring models, Read more about Next Generation SageMaker Notebooks – Now with Built-in Data Preparation, Real-Time Collaboration, and Notebook Automation[…]

New – Share ML Models and Notebooks More Easily Within Your Organization with Amazon SageMaker JumpStart

Publicada el por Stack Over Cloud

Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. SageMaker JumpStart gives you access to built-in algorithms with pre-trained models from popular model hubs, pre-trained foundation models to help you perform tasks such as article summarization and image generation, and end-to-end solutions to solve common use cases. Read more about New – Share ML Models and Notebooks More Easily Within Your Organization with Amazon SageMaker JumpStart[…]