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Common Challenges in Automated API Testing: Overcoming Obstacles with Expert Solutions

CSM Magazine

Automated API testing stands as a cornerstone in the modern software development cycle, ensuring that applications perform consistently and accurately across diverse systems and technologies. Continuous learning and adaptation are essential, as the landscape of API technology is ever-evolving.

APIs 52
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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems.

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Getting Data from your WFM System

Call Design

This is a question that is asked a lot in businesses where data needs to be extracted from various sources and collated. As technology and security increase, so too does the tightening around access and use of said data, especially within the contact centre. Which is better Direct Query or Webservice? Maintenance. Scalability.

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The Future of Debt Collection Agencies: Contact Center Technology and Customer-Centric Strategies

NobelBiz

Traditional collection methods, such as persistent phone calls and letters, are making way for more nuanced, technology-driven, and customer-oriented strategies. This evolution reflects broader trends in consumer behavior, regulatory environments, and technological advancements.

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Use Amazon SageMaker pipeline sharing to view or manage pipelines across AWS accounts

AWS Machine Learning

On August 9, 2022, we announced the general availability of cross-account sharing of Amazon SageMaker Pipelines entities. You can now use cross-account support for Amazon SageMaker Pipelines to share pipeline entities across AWS accounts and access shared pipelines directly through Amazon SageMaker API calls.

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Redact sensitive data from streaming data in near-real time using Amazon Comprehend and Amazon Kinesis Data Firehose

AWS Machine Learning

Near-real-time delivery of data and insights enable businesses to rapidly respond to their customers’ needs. Real-time data can come from a variety of sources, including social media, IoT devices, infrastructure monitoring, call center monitoring, and more. After that, documents are free of PII entities and users can consume the data.

APIs 84
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Harnessing the power of enterprise data with generative AI: Insights from Amazon Kendra, LangChain, and large language models

AWS Machine Learning

Without continued learning, these models remain oblivious to new data and trends that emerge after their initial training. Instead of relying solely on their pre-trained knowledge, RAG allows models to pull data from documents, databases, and more. Prerequisites You must have the following prerequisites: An AWS account.