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Favorite This post was co-written by Marius Cealera, Senior Partner Solutions Architect at AWS, Zdenko Estok, Cloud Architect at Accenture and Sakar Selimcan, Cloud Architect at Accenture. Machine learning (ML) is a high-stakes business priority, with companies spending $306 billion on ML applications in the past 3 years. According to
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Shared by AWS Machine Learning September 22, 2022
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
Read More Shared by AWS Machine Learning September 22, 2022
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
Read More Shared by AWS Machine Learning September 21, 2022
Favorite Pharmaceutical companies seeking approval from regulatory agencies such as the US Food & Drug Administration (FDA) or Japanese Pharmaceuticals and Medical Devices Agency (PMDA) to sell their drugs on the market must submit evidence to prove that their drug is safe and effective for its intended use. A team
Read More Shared by AWS Machine Learning September 21, 2022
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
Read More Shared by AWS Machine Learning September 21, 2022
Favorite Amazon SageMaker Autopilot has added a new training mode that supports model ensembling powered by AutoGluon. Ensemble training mode in Autopilot trains several base models and combines their predictions using model stacking. For datasets less than 100 MB, ensemble training mode builds machine learning (ML) models with high accuracy
Read More Shared by AWS Machine Learning September 21, 2022
Favorite Last year, we announced the general availability of RStudio on Amazon SageMaker, the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE, and dial up and down the underlying compute resources without interrupting your work, making it
Read More Shared by AWS Machine Learning September 20, 2022
Favorite In this post, we demonstrate how to use Amazon Polly—a leading cloud service that converts text into lifelike speech—to read the content of a webpage and highlight the content as it’s being read. Adding audio playback to a webpage improves the accessibility and visitor experience of the page. Audio-enhanced
Read More Shared by AWS Machine Learning September 17, 2022
Favorite Amazon SageMaker Automatic Model Tuning introduces Hyperband, a multi-fidelity technique to tune hyperparameters as a faster and more efficient way to find an optimal model. In this post, we show how automatic model tuning with Hyperband can provide faster hyperparameter tuning—up to three times as fast. The benefits of
Read More Shared by AWS Machine Learning September 17, 2022
Favorite Customer relationship management (CRM) is a critical tool that organizations maintain to manage customer interactions and build business relationships. Zendesk is a CRM tool that makes it easy for customers and businesses to keep in sync. Zendesk captures a wealth of customer data, such as support tickets created and
Read More Shared by AWS Machine Learning September 17, 2022