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3 Ways to Collect In-App Feedback: Webviews, SDKs & APIs

mopinion

Collecting and analysing in-app feedback can be very straightforward – provided that you have the right tools and methodology in place to do so. In a previous article, we outlined several reasons why collecting in-app feedback is important for the mobile user experience.

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Using Integrations In Customer Experience

Lumoa

Essentially, an integration makes it possible to connect different tools, APIs, or systems to build more value out of your data. For example, Lumoa has very clear open APIs and you can easily integrate into any modern platform. Send customer feedback to Lumoa You can easily send the feedback that you collect to Lumoa.

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Build a receipt and invoice processing pipeline with Amazon Textract

AWS Machine Learning

It starts with a document capture stage to securely collect and store scanned invoices and receipts. AnalyzeExpense is an API dedicated to processing invoice and receipts documents. It is available both as a synchronous or asynchronous API. It is available both as a synchronous or asynchronous API.

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Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning

The solution uses AWS Lambda , Amazon API Gateway , Amazon EventBridge , and SageMaker to automate the workflow with human approval intervention in the middle. The approver approves the model by following the link in the email to an API Gateway endpoint. API Gateway invokes a Lambda function to initiate model updates.

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Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning

This requires searching over large collections of documents with diverse content, such as website data, which can include various topics such as sustainability, leadership, financial results, and more. You have the option to override it to use either hybrid or semantic search in the API.

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How the Web of Science enables innovation in agriculture

Clarivate

CGIAR, the world’s largest global agricultural innovation network, used our Web of Science API to significantly reduce their manual workload. The tool uses APIs (Application Programming Interfaces) and, among them, the Web of Science API to make sure publications are peer-reviewed and indexed in the Web of Science Core Collection.

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Amazon SageMaker model parallel library now accelerates PyTorch FSDP workloads by up to 20%

AWS Machine Learning

In particular, we cover the SMP library’s new simplified user experience that builds on open source PyTorch Fully Sharded Data Parallel (FSDP) APIs, expanded tensor parallel functionality that enables training models with hundreds of billions of parameters, and performance optimizations that reduce model training time and cost by up to 20%.