Favorite While performing machine translations, you may have situations where you wish to preserve specific sections of text from being translated, such as names, unique identifiers, or codes. We at the Amazon Translate team are excited to announce a tag modifications that allows you to specify what text should not
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Shared by AWS Machine Learning November 6, 2020
Favorite Reinforcement learning (RL) is used to automate decision-making in a variety of domains, including games, autoscaling, finance, robotics, recommendations, and supply chain. Launched at AWS re:Invent 2018, Amazon SageMaker RL helps you quickly build, train, and deploy policies learned by RL. Ray is an open-source distributed execution framework that
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Shared by AWS Machine Learning November 5, 2020
Favorite Support tickets, customer feedback forms, user surveys, product feedback, and forum posts are some of the documents that businesses collect from their customers and employees. The applications used to collect these case documents typically include incident management systems, social media channels, customer forums, and email. Routing these cases quickly
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Shared by AWS Machine Learning November 4, 2020
Favorite Machine learning (ML) models have long been considered black boxes because predictions from these models are hard to interpret. However, recently, several frameworks aiming at explaining ML models were proposed. Model interpretation can be divided into local and global explanations. A local explanation considers a single sample and answers
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Shared by AWS Machine Learning November 4, 2020
Favorite High-quality machine learning (ML) models depend on accurately labeled, high-quality training, validation, and test data. As ML and deep learning models are increasingly integrated into production environments, it’s becoming more important than ever to have customizable, real-time data labeling pipelines that can continuously receive and process unlabeled data. For
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Shared by AWS Machine Learning November 3, 2020
Favorite There have been breakthroughs in understanding COVID-19, such as how soon an exposed person will develop symptoms and how many people on average will contract the disease after contact with an exposed individual. The wider research community is actively working on accurately predicting the percent population who are exposed,
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Shared by AWS Machine Learning October 31, 2020
Favorite Every day there is something new going on in the world of AWS Machine Learning—from launches to new to use cases to interactive trainings. We’re packaging some of the not-to-miss information from the ML Blog and beyond for easy perusing each month. Check back at the end of each
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Shared by AWS Machine Learning October 31, 2020
Favorite Model training and serving steps are two essential pieces of a successful end-to-end machine learning (ML) pipeline. These two steps often require different software and hardware setups to provide the best mix for a production environment. Model training is optimized for a low-cost, feasible total run duration, scientific flexibility,
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Shared by AWS Machine Learning October 31, 2020
Favorite Based on our day to day experience, the information we consume is entirely digital. We read the news on our mobile devices far more than we do from printed copy newspapers. Tickets for sporting events, music concerts, and airline travel are stored in apps on our phones. One could
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Shared by AWS Machine Learning October 31, 2020
Favorite Conversational interfaces like chatbots have become an important channel for brands to communicate with their customers, partners, and employees. They offer faster service, 24/7 availability, and lower service costs. By analyzing your bot’s customer conversations, you can discover challenges in user experience, trending topics, and missed utterances. These additional
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Shared by AWS Machine Learning October 30, 2020