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E80 Group secures its AGVs with Cisco industrial solutions and Italtel system integration

Cisco - Contact Center

Picture a factory floor. The air hangs heavy, thick with the metallic tang of machinery and the oil that keeps it all turning. Every square foot seems to be utilized. Rows of hulking machines dominate the space. Between them are narrow pathways that workers and machines must navigate. These are the conditions for which E80 […]

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

AWS Machine Learning

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. Just like DevOps combines development and operations for software engineering, MLOps combines ML engineering and IT operations.

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23 Inspiring Women to Watch in 2023

TechSee

Caroline Yap, Director of AI Practice, Google Cloud – Caroline’s team accelerates customer transformations with AI and Industry Solutions, including Contact Center AI (CCAI), Vertex AI, and DocAI. She is a force to be reckoned with as a writer and speaker on customer experience.

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Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

Wipro further accelerated their ML model journey by implementing Wipro’s code accelerators and snippets to expedite feature engineering, model training, model deployment, and pipeline creation. About the Authors Stephen Randolph is a Senior Partner Solutions Architect at Amazon Web Services (AWS).

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Automated exploratory data analysis and model operationalization framework with a human in the loop

AWS Machine Learning

Now we have low-code and no-code tools like Amazon SageMaker Data Wrangler , AWS Glue DataBrew , and Amazon SageMaker Canvas to assist with data feature engineering. However, a lot of these processes are still currently done manually by a data engineer or analyst who analyzes the data using these tools. SageMaker Pipeline Execution.

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How Accenture is using Amazon CodeWhisperer to improve developer productivity

AWS Machine Learning

Accenture is using Amazon CodeWhisperer to accelerate coding as part of our software engineering best practices initiative in our Velocity platform,” says Balakrishnan Viswanathan, Senior Manager, Tech Architecture at Accenture. In this post, we illustrate how Accenture uses CodeWhisperer in practice to improve developer productivity.

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Enhance call center efficiency using batch inference for transcript summarization with Amazon Bedrock

AWS Machine Learning

We also explore best practices for optimizing your batch inference workflows on Amazon Bedrock, helping you maximize the value of your data across different use cases and industries. Solution overview The batch inference feature in Amazon Bedrock provides a scalable solution for processing large volumes of data across various domains.