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.
What you'll learn
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.
Table of contents
- Challenges of evaluating the generative AI tasks - Introduction 5m
- The Art and Science of Evaluating Large Language Models 5m
- Beyond Accuracy: Mastering Evaluation Metrics for Generative AI 9m
- Best Practices for LLM Evaluation 5m
- Solving Evaluation Challenges 9m
- Streamlining Model Evaluation with Computation-based Metrics 3m
- Comparing performance with Model based evaluation 8m
- Reading List 0m
