article thumbnail

Security best practices to consider while fine-tuning models in Amazon Bedrock

AWS Machine Learning

Analyze results through metrics and evaluation. Model customization in Amazon Bedrock involves the following actions: Create training and validation datasets. Set up IAM permissions for data access. Configure a KMS key and VPC. Create a fine-tuning or pre-training job with hyperparameter tuning. Use the custom model for tasks like inference.

article thumbnail

5 Facts to End the ROI Debate on Customer Experience

Beyond Philosophy

According to the study, “the cumulative return of a $100 investment in the ACSI fund from April 2000 to April 2012 was $490, a gain of 390 percent. According to Marketing Metrics , you have a much higher probability to sell your existing customers than a new prospect, at 60 to 70% versus 5 to 20%, respectively.

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

Connecting Satisfaction With Behavior: Does The Service-Profit Chain (or The Employee Engagement-Profit Chain) Still Work?

Beyond Philosophy

Here’s a summary which encapsulates the difference between satisfaction and loyalty as metrics, expressed by Susan Wyse of Snap Surveys in a June, 2012 post: “Customer Satisfaction is a measurement of customer attitudes regarding products, services, and brands. Coincidentally, this definition was also done in a June, 2012 article.

article thumbnail

Combine keyword and semantic search for text and images using Amazon Bedrock and Amazon OpenSearch Service

AWS Machine Learning

A seamless search journey not only enhances the overall user experience, but also directly impacts key business metrics such as conversion rates, average order value, and customer loyalty. Customers today expect to find products quickly and efficiently through intuitive search functionality.

article thumbnail

25 Call Center Leaders Share the Most Effective Ways to Boost Contact Center Efficiency

Callminer

Source: Human Resource Management; Issue: 51(4); 2012; Pages 535-548. Metrics, Measure, and Monitor – Make sure your metrics and associated goals are clear and concise while aligning with efficiency and effectiveness. Make each metric public and ensure everyone knows why that metric is measured. Jeff Greenfield.

article thumbnail

Best practices for Meta Llama 3.2 multimodal fine-tuning on Amazon Bedrock

AWS Machine Learning

The models were evaluated using the SQuAD F1 score metric , which measures the word-level overlap between generated responses and reference answers. These validation metrics serve as early indicators of how your fine-tuned model performs on unseen data, providing additional performance insights during fine-tuning.

article thumbnail

Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning

Distance metric : Select Euclidean. When you created your vector index earlier, you defined the similarity between vector distances to be calculated using the Euclidian metric with the nmslib engine. For more information on managing credentials securely, see the AWS Boto3 documentation. Vector field name : Enter a name, such as vector.