Remove Analytics Remove Examples Remove industry solution
article thumbnail

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

AWS Machine Learning

Now that you’ve gone through the creation and initial deployment, the MLOps engineer can configure failure alerts to be alerted for issues, for example, when a pipeline fails to do its intended job. He is an evangelist who loves to help customers leverage new technologies and build repeatable industry solutions to solve their problems.

Analytics 128
article thumbnail

Reinvent personalization with generative AI on Amazon Bedrock using task decomposition for agentic workflows

AWS Machine Learning

The following is an example of a synthetically generated offering for the construction industry: OneCompany Consulting Construction Consulting Services Offerings Introduction OneCompany Consulting is a premier construction consulting firm dedicated to. Construction Technology Solutions - Construction Data Analytics and Reporting.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

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.

article thumbnail

Build an agronomic data platform with Amazon SageMaker geospatial capabilities

AWS Machine Learning

These platforms help farmers make sense of their data by integrating information from multiple sources for use in visualization and analytics applications. The following example user interface demonstrates how a builder of agronomic data platforms may integrate insights delivered by SageMaker geospatial capabilities.

APIs 91
article thumbnail

Why South Africa CX is Taking Over the Global Call Center Conversation

Outsource Consultants

This growth extends beyond traditional voice services to include complex back-office processes, digital services, and specialized industry solutions. Government Backing Fuels Growth The South African government recognizes the BPO industry’s potential as a key driver of economic growth and job creation.

article thumbnail

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

AWS Machine Learning

To demonstrate the orchestrated workflow, we use an example dataset regarding diabetic patient readmission. You can try out the approach with this example and experiment with additional data transformations following similar steps with your own datasets. For more information, refer to Amazon SageMaker Identity-Based Policy Examples.

article thumbnail

Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

The drift notification emails will look similar to the examples in Figure 8. About the Authors Stephen Randolph is a Senior Partner Solutions Architect at Amazon Web Services (AWS). He holds the AWS AI/ML Specialty certification and authors technical blogs on AI/ML services and solutions.