Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation

This course equips machine learning practitioners with the essential tools, techniques, and best practices for evaluating both generative and predictive AI models. Model evaluation is a critical discipline for ensuring that ML systems deliver reliable, accurate, and high-performing results in production. Participants will gain a deep understanding of various evaluation metrics, methodologies, and their appropriate application across different model types and tasks. The course will emphasize the unique challenges posed by generative AI models and provide strategies for tackling them effectively. By leveraging Google Cloud's Vertex AI platform, participants will learn how to implement robust evaluation processes for model selection, optimization, and continuous monitoring.

• Welcome to the Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
• Welcome to the course
• Introduction to Model Evaluation
• Introduction to Model Evaluation
• Model Evaluation within MLOps
• Model Evaluation Challenges and Solutions offered by Vertex AI
• MLOps: Introduction to Model Evaluation Quiz
• Reading List
• Model Evaluation for Generative AI
• Challenges of evaluating the generative AI tasks - Introduction
• The Art and Science of Evaluating Large Language Models
• Beyond Accuracy: Mastering Evaluation Metrics for Generative AI
• Best Practices for LLM Evaluation
• Solving Evaluation Challenges
• Streamlining Model Evaluation with Computation-based Metrics
• Comparing performance with Model based evaluation
• MLOps: Model Evaluation for Generative AI Quiz
• Reading List
• Course Summary
• Course Summary
• Your Next Steps
• Course Badge