Remove templates product-feature-support-troubleshooting
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Live Meeting Assistant with Amazon Transcribe, Amazon Bedrock, and Knowledge Bases for Amazon Bedrock

AWS Machine Learning

See CHANGELOG for latest features and fixes. Solution overview The LMA sample solution captures speaker audio and metadata from your browser-based meeting app (as of this writing, Zoom and Chime are supported), or audio only from any other browser-based meeting app, softphone, or audio source.

APIs 109
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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

One of the key drivers of Philips’ innovation strategy is artificial intelligence (AI), which enables the creation of smart and personalized products and services that can improve health outcomes, enhance customer experience, and optimize operational efficiency. Once deployed, model performance is continuously monitored.

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Driving advanced analytics outcomes at scale using Amazon SageMaker powered PwC’s Machine Learning Ops Accelerator

AWS Machine Learning

However, putting an ML model into production at scale is challenging and requires a set of best practices. Many businesses already have data scientists and ML engineers who can build state-of-the-art models, but taking models to production and maintaining the models at scale remains a challenge. It’s much more than just automation.

Analytics 105
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The Ultimate Client Onboarding Checklist for CS Teams

Totango

A lot goes into crafting the ideal onboarding process for SaaS products. At the same time, you need to minimize time-to-value (TTV) to ensure customers see the benefits of your product as soon as possible. Introducing navigational features. Guiding customers through how to use basic features. Completing profiles.

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Use the Amazon SageMaker and Salesforce Data Cloud integration to power your Salesforce apps with AI/ML

AWS Machine Learning

This post is co-authored by Daryl Martis, Director of Product, Salesforce Einstein AI. In this post, we expand on this topic to demonstrate how to use Einstein Studio for product recommendations. This is the second post in a series discussing the integration of Salesforce Data Cloud and Amazon SageMaker.

APIs 78
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25 Customer Service Email Templates that Generate Trust and Loyalty

Nicereply

Together with Influx , we have compiled 25 of our favorite customer service email templates for both delicate and often-repeated customer service interactions. In this blog post you will find 25 customer service email templates: Welcome email. Customer Service Email Templates – Welcome email template.

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Qualitative vs. quantitative research: What’s the difference?

delighted

And, understanding that difference can make a large impact on how you analyze the success of a product, service update, or overall company performance. It can explain the “ what” as outlined in quantitative data, helping you to troubleshoot issues and create new ideas for research. Use quantitative research to test a hypothesis.

Surveys 78