AWS Machine Learning Blog
Search for knowledge in Quip documents with intelligent search using the Quip connector for Amazon Kendra
Organizations use collaborative document authoring solutions like Salesforce Quip to embed real-time, collaborative documents inside Salesforce records. Quip is Salesforce’s productivity platform that transforms the way enterprises work together, delivering modern collaboration securely and simply across any device. A Quip repository captures invaluable organizational knowledge in the form of collaborative documents and workflows. However, finding […]
Read MoreIntegrate ServiceNow with Amazon Lex chatbot for ticket processing
Conversational interfaces (or chatbots) can provide an intuitive interface for processes such as creating and monitoring tickets. Let’s consider a situation in which a recent hire on your team is required to cut tickets for office equipment. To do so, they have to interact with a ticketing software that the organization uses. This often requires […]
Read MoreFine-tune and deploy a Wav2Vec2 model for speech recognition with Hugging Face and Amazon SageMaker
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 clips as input and convert speech […]
Read MoreBuild a virtual credit approval agent with Amazon Lex, Amazon Textract, and Amazon Connect
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 consider borrowers, who are waiting for […]
Read MoreControl access to Amazon SageMaker Feature Store offline using AWS Lake Formation
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 feature pipelines for different projects and […]
Read MoreManage dialog to elicit Amazon Lex slots in Amazon Connect contact flows
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 contact center. In both the self-service […]
Read MoreBuild a custom entity recognizer for PDF documents using Amazon Comprehend
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 be error-prone and time-consuming. Rule-based software […]
Read MoreGetting started with the Amazon Kendra Box connector
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 their content storage and lifecycle management […]
Read MoreReceive notifications for image analysis with Amazon Rekognition Custom Labels and analyze predictions
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 started by simply uploading tens of […]
Read MoreCustomize the Amazon SageMaker XGBoost algorithm container
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 powerful algorithm to accommodate different requirements. […]
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