Evaluating and Debugging Generative AI
1h 12mIntermediate2024-07-25
Authors
Kesha Williams
Software Engineering Manager, Speaker, Tech Blogger
Course details
Generative AI and large language models (LLMs) are changing how we build AI-powered solutions. In this course, learn the tools needed to evaluate and debug generative AI models while boosting productivity. Instructor Kesha Williams details the tools that help you train, evaluate, debug, trace, and monitor generative AI models. Learn to evaluate and debug LLMs you access via an API, fine-tune yourself, or train from scratch. By the end of this course, you’ll have a solid understanding of evaluating and debugging models.
Learning objectives
Understand the process to evaluate, debug, and monitor LLM models that are accessed via an API, like ChatGPT.
Explore the steps to evaluate, debug, and monitor a LLM during the fine-tuning process.
Evaluate, debug, and monitor a generative AI model that you train from scratch.
Employ tools that help manage the lifecycle of generative AI models.
Understand the differences between machine learning operations (MLOps) and large language model operations (LLMOps).
Set up a local development environment and gain access to the tools needed for evaluating, debugging, and monitoring.
Learning objectives
Understand the process to evaluate, debug, and monitor LLM models that are accessed via an API, like ChatGPT.
Explore the steps to evaluate, debug, and monitor a LLM during the fine-tuning process.
Evaluate, debug, and monitor a generative AI model that you train from scratch.
Employ tools that help manage the lifecycle of generative AI models.
Understand the differences between machine learning operations (MLOps) and large language model operations (LLMOps).
Set up a local development environment and gain access to the tools needed for evaluating, debugging, and monitoring.
Skills covered
Programming FoundationsGenerative AISoftware Development ToolsArtificial Intelligence (AI)Software DevelopmentOne-Off
Concepts
Introduction
- Introduction to evaluating and debugging GenAI
Exploring Generative AI Models
- Explore generative AI models
- Analyzing the Transformer architecture
Evaluating Generative AI Models
- Understand evaluation metrics
- Apply model analysis techniques
- Examine metric applications
- Challenge - Evaluate image quality
- Solution - Evaluate image quality
- Challenge - Analyze text output
- Solution - Analyze text output
Debugging and Troubleshooting Generative AI Models
- Identify common model issues
- Implement troubleshooting techniques
- Explore troubleshooting cases
- Challenge - Remedy mode collapse
- Solution - Remedy mode collapse
- Challenge - Correct vanishing gradients
- Solution - Correct vanishing gradients
Discussing Ethics and Ensuring Fairness
- Discuss ethical implications
- Develop bias mitigation strategies
- Propose ethical guidelines
- Challenge - Implement bias mitigation
- Solution - Implement bias mitigation
Conclusion
- Strategize scalability and deployment
- Your evaluating and debugging GenAI journey