Processing auto insurance claims at scale using Amazon Rekognition Custom Labels and Amazon SageMaker Ground Truth

Favorite Computer vision uses machine learning (ML) to build applications that process images or videos. With Amazon Rekognition, you can use pre-trained computer vision models to identify objects, people, text, activities, or inappropriate content. Our customers have use cases that span every industry, including media, finance, manufacturing, sports, and technology.

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Shared by AWS Machine Learning October 16, 2020

Building a medical image search platform on AWS

Favorite Improving radiologist efficiency and preventing burnout is a primary goal for healthcare providers. A nationwide study published in Mayo Clinic Proceedings in 2015 showed radiologist burnout percentage at a concerning 61% [1]. In additon, the report concludes that “burnout and satisfaction with work-life balance in US physicians worsened from

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Shared by AWS Machine Learning October 15, 2020

Amazon Personalize improvements reduce model training time by up to 40% and latency for generating recommendations by up to 30%

Favorite We’re excited to announce new efficiency improvements for Amazon Personalize. These improvements decrease the time required to train solutions (the machine learning models trained with your data) by up to 40% and reduce the latency for generating real-time recommendations by up to 30%. Amazon Personalize enables you to build

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Shared by AWS Machine Learning October 14, 2020

Optimizing the cost of training AWS DeepRacer reinforcement learning models

Favorite AWS DeepRacer is a cloud-based 3D racing simulator, an autonomous 1/18th scale race car driven by reinforcement learning, and a global racing league. Reinforcement learning (RL), an advanced machine learning (ML) technique, enables models to learn complex behaviors without labeled training data and make short-term decisions while optimizing for longer-term goals. But as

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Shared by AWS Machine Learning October 14, 2020

Using speaker diarization for streaming transcription with Amazon Transcribe and Amazon Transcribe Medical

Favorite Conversational audio data that requires transcription, such as phone calls, doctor visits, and online meetings, often has multiple speakers. In these use cases, it’s important to accurately label the speaker and associate them to the audio content delivered. For example, you can distinguish between a doctor’s questions and a

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Shared by AWS Machine Learning October 14, 2020