Favorite Model training forms the core of any machine learning (ML) project, and having a trained ML model is essential to adding intelligence to a modern application. A performant model is the output of a rigorous and diligent data science methodology. Not implementing a proper model training process can lead

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Shared by AWS Machine Learning October 6, 2022

Favorite Synamedia is a leading video technology provider addressing the needs for premium video service providers and direct-to-consumer (D2C) with a comprehensive solution portfolio. Synamedia solutions spread across several pillars such as video networks, TV platforms, advertisement and monetization, and content protection and piracy disruption. Synamedia partnered with AWS to

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Shared by AWS Machine Learning October 6, 2022

Favorite Near-real-time delivery of data and insights enable businesses to rapidly respond to their customers’ needs. Real-time data can come from a variety of sources, including social media, IoT devices, infrastructure monitoring, call center monitoring, and more. Due to the breadth and depth of data being ingested from multiple sources,

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Shared by AWS Machine Learning October 5, 2022

Favorite Face-off Probability is the National Hockey League’s (NHL) first advanced statistic using machine learning (ML) and artificial intelligence. It uses real-time Player and Puck Tracking (PPT) data to show viewers which player is likely to win a face-off before the puck is dropped, and provides broadcasters and viewers the

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Shared by AWS Machine Learning October 5, 2022

Favorite Machine learning (ML) has improved business across industries in recent years—from the recommendation system on your Prime Video account, to document summarization and efficient search with Alexa’s voice assistance. However, the question remains of how to incorporate this technology into your business. Unlike traditional rule-based methods, ML automatically infers

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Shared by AWS Machine Learning October 4, 2022

Favorite Creating robust and reusable machine learning (ML) pipelines can be a complex and time-consuming process. Developers usually test their processing and training scripts locally, but the pipelines themselves are typically tested in the cloud. Creating and running a full pipeline during experimentation adds unwanted overhead and cost to the

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Shared by AWS Machine Learning October 4, 2022

Favorite Amazon Elastic Compute Cloud (Amazon EC2) G5 instances are the first and only instances in the cloud to feature NVIDIA A10G Tensor Core GPUs, which you can use for a wide range of graphics-intensive and machine learning (ML) use cases. With G5 instances, ML customers get high performance and

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Shared by AWS Machine Learning October 3, 2022

Favorite This post is a joint collaboration with Andries Engelbrecht and James Sun of Snowflake, Inc. The cloud computing revolution has enabled businesses to capture and retain corporate and organizational data without capacity planning or data retention constraints. Now, with diverse and vast reserves of longitudinal data, companies are increasingly

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Shared by AWS Machine Learning October 3, 2022

Favorite In this post, we demonstrate how Kubeflow on AWS (an AWS-specific distribution of Kubeflow) used with AWS Deep Learning Containers and Amazon Elastic File System (Amazon EFS) simplifies collaboration and provides flexibility in training deep learning models at scale on both Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon

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Shared by AWS Machine Learning October 1, 2022

Favorite AWS Panorama is a collection of machine learning (ML) devices and a software development kit (SDK) that brings computer vision to on-premises internet protocol (IP) cameras. AWS Panorama device options include the AWS Panorama Appliance and the Lenovo ThinkEdge SE70, powered by AWS Panorama. These device options provide you

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Shared by AWS Machine Learning October 1, 2022