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6 Online Data Analyst Courses

JivoChat

Data-driven decisions are essential in businesses to diminish the chances of errors, and online data analyst courses will teach you how to interpret data precisely. Check out the article to know more about the courses that can help you boost your career, and increase your chances of creating successful projects. Workload: 20.5

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

AWS Machine Learning

ML Engineer at Tiger Analytics. 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.

APIs 99
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Build a multilingual automatic translation pipeline with Amazon Translate Active Custom Translation

AWS Machine Learning

We demonstrate how to use the AWS Management Console and Amazon Translate public API to deliver automatic machine batch translation, and analyze the translations between two language pairs: English and Chinese, and English and Spanish. In this post, we present a solution that D2L.ai

APIs 75
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Deploy self-service question answering with the QnABot on AWS solution powered by Amazon Lex with Amazon Kendra and large language models

AWS Machine Learning

To help you get started, we’ve also released a set of sample one-click deployable Lambda functions ( plugins ) to integrate QnABot with your choice of leading LLM providers, including our own Amazon Bedrock service and APIs from third-party providers, Anthropic and AI21. We expect to add more sample plugins over time.

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Pros and Cons of Using the Built-in Front CSAT Solution

Nicereply

Pro: Analytics. The good thing about analytics is that you don’t need to go to any third-party solution. And of course, it’s a “comfortable solution”, as you don’t have to log in to another application to see your data. You have ratings, comments, and analytics in one place. Con: Basic analytics.

Surveys 111
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How Sportradar used the Deep Java Library to build production-scale ML platforms for increased performance and efficiency

AWS Machine Learning

In this case, it detects the DJL PyTorch engine implementation, which will act as the bridge between the DJL API and the PyTorch Native. Every operation in the DJL API is hand-crafted to best fit the Java conventions and make it easily accessible. The engine then works to load the PyTorch Native.

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What CTOs Should Know Before Implementing Conversational AI in the Contact Center

SmartAction

When used in business, conversational artificial intelligence (AI) supports overall call center operations by providing self-service options, 24/7 availability, and real-time data and analytics – while lowering costs and increasing profits. It linked via API to internal data sources and current customer input to find a successful solution.