Accelerate your identity verification projects using AWS Amplify and Amazon Rekognition sample implementations

Favorite Amazon Rekognition allows you to mitigate fraudulent attacks and minimize onboarding friction for legitimate customers through a streamlined identity verification process. This can result in an increase in customer trust and safety. Key capabilities of this solution include: Register a new user using a selfie Register a new user

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Shared by AWS Machine Learning July 19, 2022

Google at ICML 2022

Favorite Posted by Cat Armato, Program Manager, University Relations Google is a leader in machine learning (ML) research with groups innovating across virtually all aspects of the field, from theory to application. We build machine learning systems to solve deep scientific and engineering challenges in areas of language, music, visual

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Shared by Google AI Technology July 18, 2022

Build a predictive maintenance solution with Amazon Kinesis, AWS Glue, and Amazon SageMaker

Favorite Organizations are increasingly building and using machine learning (ML)-powered solutions for a variety of use cases and problems, including predictive maintenance of machine parts, product recommendations based on customer preferences, credit profiling, content moderation, fraud detection, and more. In many of these scenarios, the effectiveness and benefits derived from

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Shared by AWS Machine Learning July 15, 2022

Track your ML experiments end to end with Data Version Control and Amazon SageMaker Experiments

Favorite Data scientists often work towards understanding the effects of various data preprocessing and feature engineering strategies in combination with different model architectures and hyperparameters. Doing so requires you to cover large parameter spaces iteratively, and it can be overwhelming to keep track of previously run configurations and results while

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Shared by AWS Machine Learning July 15, 2022

Towards Reliability in Deep Learning Systems

Favorite Posted by Dustin Tran and Balaji Lakshminarayanan, Research Scientists, Google Research Deep learning models have made impressive progress in vision, language, and other modalities, particularly with the rise of large-scale pre-training. Such models are most accurate when applied to test data drawn from the same distribution as their training

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Shared by Google AI Technology July 14, 2022