Favorite Banking and financial institutions review thousands of credit applications per week. The credit approval process requires financial organizations to invest time and resources in reviewing documents like W2s, bank statements, and utility bills. The overall experience can be costly for the organization. At the same time, organizations have to

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Shared by AWS Machine Learning April 16, 2022

Favorite Automatic speech recognition (ASR) is a commonly used machine learning (ML) technology in our daily lives and business scenarios. Applications such as voice-controlled assistants like Alexa and Siri, and voice-to-text applications like automatic subtitling for videos and transcribing meetings, are all powered by this technology. These applications take audio

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Shared by AWS Machine Learning April 16, 2022

Favorite Amazon Lex can add powerful automation to contact center solutions, so you can enable self-service via interactive voice response (IVR) interactions or route calls to the appropriate agent based on caller input. These capabilities can increase customer satisfaction by streamlining the user experience, and improve containment rates in the

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Shared by AWS Machine Learning April 14, 2022

Favorite You can establish feature stores to provide a central repository for machine learning (ML) features that can be shared with data science teams across your organization for training, batch scoring, and real-time inference. Data science teams can reuse features stored in the central repository, avoiding the need to reengineer

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Shared by AWS Machine Learning April 14, 2022

Favorite Amazon Kendra is a highly accurate and easy-to-use intelligent search service powered by machine learning (ML). Amazon Kendra offers a suite of data source connectors to simplify the process of ingesting and indexing your content, wherever it resides. For many organizations, Box Content Cloud is a core part of

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Shared by AWS Machine Learning April 9, 2022

Favorite In many industries, it’s critical to extract custom entities from documents in a timely manner. This can be challenging. Insurance claims, for example, often contain dozens of important attributes (such as dates, names, locations, and reports) sprinkled across lengthy and dense documents. Manually scanning and extracting such information can

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Shared by AWS Machine Learning April 9, 2022

Favorite Amazon Rekognition Custom Labels is a fully managed computer vision service that allows developers to build custom models to classify and identify objects in images that are specific and unique to your business. Rekognition Custom Labels doesn’t require you to have any prior computer vision expertise. You can get

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Shared by AWS Machine Learning April 7, 2022

Favorite Research over the past few years has shown that machine learning (ML) models are vulnerable to adversarial inputs, where an adversary can craft inputs to strategically alter the model’s output (in image classification, speech recognition, or fraud detection). For example, imagine you have deployed a model that identifies your

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Shared by AWS Machine Learning April 6, 2022

Favorite The built-in Amazon SageMaker XGBoost algorithm provides a managed container to run the popular XGBoost machine learning (ML) framework, with added convenience of supporting advanced training or inference features like distributed training, dataset sharding for large-scale datasets, A/B model testing, or multi-model inference endpoints. You can also extend this

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Shared by AWS Machine Learning April 6, 2022

Favorite Customer service calls require customer agents to have the customer’s account information to process the caller’s request. For example, to provide a status on an insurance claim, the support agent needs policy holder information such as the policy ID and claim number. Such information is often collected in the

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Shared by AWS Machine Learning April 5, 2022