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42 Best Customer Feedback Software for 2022

ProProfs Blog

Yes, you can collect their feedback on your brand offerings with simple questions like: Are you happy with our products or services? Various customer feedback tools help you track your customers’ pulse consistently. What Is a Customer Feedback Tool. Read more: 12 Channels to Capture Customer Feedback. Here we go!

Feedback 148
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Create powerful self-service experiences with Amazon Lex on Talkdesk CX Cloud contact center

AWS Machine Learning

The benefits of Amazon Lex and Talkdesk CX Cloud are exemplified by WaFd Bank , a full-service commercial US bank in 200 locations and managing $20 billion in assets. The bank has invested in a digital transformation of its contact center to provide exceptional service to its clients.

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Capital One Announces Launch of DevExchange / Offers New APIs

Natalie Petouhof

They are starting something new again by becoming one of the first banks to open their platform to external developers and partners. Foundational things like: APIs that matter, are easy to integrate and are standards-based. A place where feedback matters and there is an opportunity to explore ideas with like-minded people.

APIs 40
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Connecting Amazon Redshift and RStudio on Amazon SageMaker

AWS Machine Learning

Users can also interact with data with ODBC, JDBC, or the Amazon Redshift Data API. This blog focuses on the Rstudio on Amazon SageMaker language, with business analysts, data engineers, data scientists, and all developers that use the R Language and Amazon Redshift, as the target audience. Prerequisites. About the Authors.

APIs 102
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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

With SageMaker MLOps tools, teams can easily train, test, troubleshoot, deploy, and govern ML models at scale to boost productivity of data scientists and ML engineers while maintaining model performance in production. When the model is ready and approved for use, it’s deployed into the real-world production systems.

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

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Zero-shot and few-shot prompting for the BloomZ 176B foundation model with the simplified Amazon SageMaker JumpStart SDK

AWS Machine Learning

Prompt engineering for zero-shot and few-shot NLP tasks on BLOOM models Prompt engineering deals with creating high-quality prompts to guide the model towards the desired responses. Prompt engineering can greatly improve the performance of zero-shot and few-shot learning models. He is currently a Senior Adviser of CITIC CLSA.