Creating an intelligent ticket routing solution using Slack, Amazon AppFlow, and Amazon Comprehend

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

Explaining Amazon SageMaker Autopilot models with SHAP

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

Real-time data labeling pipeline for ML workflows using Amazon SageMaker Ground Truth

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

Training and serving H2O models using Amazon SageMaker

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

Building a real-time conversational analytics platform for Amazon Lex bots

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