Remove Best practices Remove Engineering Remove Metrics
article thumbnail

20 Call Center Pros Share the Most Undervalued Call Center Metrics and How To Better Leverage Them

Callminer

From essentials like average handle time to broader metrics such as call center service levels , there are dozens of metrics that call center leaders and QA teams must stay on top of, and they all provide visibility into some aspect of performance. Kaye Chapman @kayejchapman. First contact resolution (FCR) measures might be…”.

article thumbnail

Best practices for Amazon SageMaker HyperPod task governance

AWS Machine Learning

In this post, we provide best practices to maximize the value of SageMaker HyperPod task governance and make the administration and data science experiences seamless. As a best practice, set the fair-share weight higher for teams that will require access to capacity sooner than other teams.

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

Achieving Excellence: Best Practices for Contact Center Performance and Quality Assurance

Hodusoft

Achieving Excellence: Best Practices for Contact Center Performance and Quality Assurance Whether you are an entrepreneur or a professional in the contact center industry or any other sector, you know that implementing best practices can enhance performance by leaps and bounds and drive success. They create them.”

article thumbnail

Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning

Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. Security – The solution uses AWS services and adheres to AWS Cloud Security best practices so your data remains within your AWS account.

article thumbnail

LLM-as-a-judge on Amazon Bedrock Model Evaluation

AWS Machine Learning

This approach allows organizations to assess their AI models effectiveness using pre-defined metrics, making sure that the technology aligns with their specific needs and objectives. Curated judge models : Amazon Bedrock provides pre-selected, high-quality evaluation models with optimized prompt engineering for accurate assessments.

Metrics 93
article thumbnail

Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

In this post, we provide an introduction to text to SQL (Text2SQL) and explore use cases, challenges, design patterns, and best practices. Effective prompt engineering is key to developing natural language to SQL systems. Prompt engineering – The model is trained to complete prompts designed to prompt the target SQL syntax.

article thumbnail

Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning

For automatic model evaluation jobs, you can either use built-in datasets across three predefined metrics (accuracy, robustness, toxicity) or bring your own datasets. Regular evaluations allow you to adjust and steer the AI’s behavior based on feedback and performance metrics.

APIs 109