TensorStore for High-Performance, Scalable Array Storage

Favorite Posted by Jeremy Maitin-Shepard and Laramie Leavitt, Software Engineers, Connectomics at Google Many exciting contemporary applications of computer science and machine learning (ML) manipulate multidimensional datasets that span a single large coordinate system, for example, weather modeling from atmospheric measurements over a spatial grid or medical imaging predictions from

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Shared by Google AI Technology September 22, 2022

Amazon Comprehend Targeted Sentiment adds synchronous support

Favorite Earlier this year, Amazon Comprehend, a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text, launched the Targeted Sentiment feature. With Targeted Sentiment, you can identify groups of mentions (co-reference groups) corresponding to a single real-world entity or attribute, provide the sentiment associated

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Shared by AWS Machine Learning September 22, 2022

View Synthesis with Transformers

Favorite Posted by Carlos Esteves and Ameesh Makadia, Research Scientists, Google Research A long-standing problem in the intersection of computer vision and computer graphics, view synthesis is the task of creating new views of a scene from multiple pictures of that scene. This has received increased attention [1, 2, 3]

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Shared by Google AI Technology September 21, 2022

Churn prediction using Amazon SageMaker built-in tabular algorithms LightGBM, CatBoost, TabTransformer, and AutoGluon-Tabular

Favorite Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. These algorithms and models can be used for both supervised and unsupervised learning. They can process various

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Shared by AWS Machine Learning September 21, 2022

Configure a custom Amazon S3 query output location and data retention policy for Amazon Athena data sources in Amazon SageMaker Data Wrangler

Favorite Amazon SageMaker Data Wrangler reduces the time that it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio, the first fully integrated development environment (IDE) for ML. With Data Wrangler, you can simplify the process of data preparation and feature

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Shared by AWS Machine Learning September 21, 2022