AWS Machine Learning Blog

Category: Artificial Intelligence

Join AWS and NVIDIA at GTC, October 5–9

Starting Monday, October 5, 2020, the NVIDIA GPU Technology Conference (GTC) is offering online sessions for you to learn AWS best practices to accomplish your machine learning (ML), virtual workstations, high performance computing (HPC), and internet of things (IoT) goals faster and more easily. Amazon Elastic Compute Cloud (Amazon EC2) instances powered by NVIDIA GPUs […]

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Building an end-to-end intelligent document processing solution using AWS

As organizations grow larger in size, so does the need for having better document processing. In industries such as healthcare, legal, insurance, and banking, the continuous influx of paper-based or PDF documents (like invoices, health charts, and insurance claims) have pushed businesses to consider evolving their document processing capabilities. In such scenarios, businesses and organizations […]

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Creating a multi-department enterprise search using custom attributes in Amazon Kendra

An enterprise typically houses multiple departments such as engineering, finance, legal, and marketing, creating a growing number of documents and content that employees need to access. Creating a search experience that intuitively delivers the right information according to an employee’s role, and the department is critical to driving productivity and ensuring security. Amazon Kendra is a […]

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Getting started with AWS DeepRacer community races

AWS DeepRacer allows you to get hands-on with machine learning (ML) through a fully autonomous 1/18th scale race car driven by reinforcement learning, a 3D racing simulator on the AWS DeepRacer console, a global racing league, and hundreds of customer-initiated community races. With AWS DeepRacer community races, you can create your own race and invite […]

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Onboarding Amazon SageMaker Studio with AWS SSO and Okta Universal Directory

In 2019, AWS announced Amazon SageMaker Studio, a unified integrated development environment (IDE) for machine learning (ML) development. You can write code, track experiments, visualize data, and perform debugging and monitoring within a single, integrated visual interface. Amazon SageMaker Studio supports a single sign-on experience with AWS Single Sign-On (AWS SSO) authentication. External identity provider […]

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Halloween-themed AWS DeepComposer Chartbusters Challenge: Track or Treat

We are back with a spooktacular AWS DeepComposer Chartbusters challenge, Track or Treat! In this challenge, you can interactively collaborate with the ghost in the machine (learning) and compose spooky music! Chartbusters is a global monthly challenge where you can use AWS DeepComposer to create original compositions on the console using machine learning techniques, compete […]

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Running on-demand, serverless Apache Spark data processing jobs using Amazon SageMaker managed Spark containers and the Amazon SageMaker SDK

Apache Spark is a unified analytics engine for large scale, distributed data processing. Typically, businesses with Spark-based workloads on AWS use their own stack built on top of Amazon Elastic Compute Cloud (Amazon EC2), or Amazon EMR to run and scale Apache Spark, Hive, Presto, and other big data frameworks. This is useful for persistent […]

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This month in AWS Machine Learning: September 2020 edition

Every day there is something new going on in the world of AWS Machine Learning—from launches to new use cases to interactive trainings. We’re packaging some of the not-to-miss information from the ML Blog and beyond for easy perusing each month. Check back at the end of each month for the latest roundup. Launches This […]

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Using Amazon Rekognition Custom Labels and Amazon A2I for detecting pizza slices and augmenting predictions

Customers need machine learning (ML) models to detect objects that are interesting for their business. In most cases doing so is hard as these models need thousands of labeled images and deep learning expertise.  Generating this data can take months to gather, and can require large teams of labelers to prepare it for use. In […]

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Building custom language models to supercharge speech-to-text performance for Amazon Transcribe

Amazon Transcribe is a fully-managed automatic speech recognition service (ASR) that makes it easy to add speech-to-text capabilities to voice-enabled applications. As our service grows, so does the diversity of our customer base, which now spans domains such as insurance, finance, law, real estate, media, hospitality, and more. Naturally, customers in different market segments have […]

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