AWS Machine Learning Blog

Category: Artificial Intelligence

Transforming qualitative research by automating speech to text-to-text analytics

This post is authored by Satish Jha, Intelligent Automation Manager, Matt Docherty, Data Science Manager, Jayesh Muley, Associate Consultant and Tapan Vora, Rapid Prototyping, from ZS Associates. At ZS Associates, we do a significant amount of qualitative market research. The work involves interviewing relevant subjects (such as healthcare professionals and sales representatives) and developing bespoke […]

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Build a cold start time series forecasting engine using AutoGluon

Whether you’re allocating resources more efficiently for web traffic, forecasting patient demand for staffing needs, or anticipating sales of a company’s products, forecasting is an essential tool across many businesses. One particular use case, known as cold start forecasting, builds forecasts for a time series that has little or no existing historical data, such as […]

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Enable the visually impaired to hear documents using Amazon Textract and Amazon Polly

At the 2021 AWS re:Invent conference in Las Vegas, we demoed Read For Me at the AWS Builders Fair—a website that helps the visually impaired hear documents. For better quality, view the video here. Adaptive technology and accessibility features are often expensive, if they’re available at all. Audio books help the visually impaired read. Audio […]

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Announcing the AWS DeepRacer League 2022

Unleash the power of machine learning (ML) through hands-on learning and compete for prizes and glory. The AWS DeepRacer League is the world’s first global autonomous racing competition driven by reinforcement learning; bringing together students, professionals, and enthusiasts from almost every continent. I’m Tomasz Ptak, a senior software engineer at Duco, an AWS Machine Learning […]

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Train 175+ billion parameter NLP models with model parallel additions and Hugging Face on Amazon SageMaker

The last few years have seen rapid development in the field of natural language processing (NLP). While hardware has improved, such as with the latest generation of accelerators from NVIDIA and Amazon, advanced machine learning (ML) practitioners still regularly run into issues scaling their large language models across multiple GPU’s. In this blog post, we […]

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ML inferencing at the edge with Amazon SageMaker Edge and Ambarella CV25

Ambarella builds computer vision SoCs (system on chips) based on a very efficient AI chip architecture and CVflow that provides the Deep Neural Network (DNN) processing required for edge inferencing use cases like intelligent home monitoring and smart surveillance cameras. Developers convert models trained with frameworks (such as TensorFlow or MXNET) to Ambarella CVflow format […]

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Anomaly detection with Amazon SageMaker Edge Manager using AWS IoT Greengrass V2

Deploying and managing machine learning (ML) models at the edge requires a different set of tools and skillsets as compared to the cloud. This is primarily due to the hardware, software, and networking restrictions at the edge sites. This makes deploying and managing these models more complex. An increasing number of applications, such as industrial […]

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How Kustomer utilizes custom Docker images & Amazon SageMaker to build a text classification pipeline

This is a guest post by Kustomer’s Senior Software & Machine Learning Engineer, Ian Lantzy, and AWS team Umesh Kalaspurkar, Prasad Shetty, and Jonathan Greifenberger. In Kustomer’s own words, “Kustomer is the omnichannel SaaS CRM platform reimagining enterprise customer service to deliver standout experiences. Built with intelligent automation, we scale to meet the needs of […]

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Build, train, and deploy Amazon Lookout for Equipment models using the Python Toolbox

Predictive maintenance can be an effective way to prevent industrial machinery failures and expensive downtime by proactively monitoring the condition of your equipment, so you can be alerted to any anomalies before equipment failures occur. Installing sensors and the necessary infrastructure for data connectivity, storage, analytics, and alerting are the foundational elements for enabling predictive […]

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Choose the best data source for your Amazon SageMaker training job

Amazon SageMaker is a managed service that makes it easy to build, train, and deploy machine learning (ML) models. Data scientists use SageMaker training jobs to easily train ML models; you don’t have to worry about managing compute resources, and you pay only for the actual training time. Data ingestion is an integral part of […]

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