09
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
09
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
These skills were generated by AI. Do you agree this course teaches these skills?
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.
Course Info
Objectives
- Understand the nuances of model evaluation in both predictive and generative AI, recognizing its crucial role within the MLOps lifecycle.
- Identify and apply appropriate evaluation metrics for different generative AI tasks.
- Efficiently evaluate generative AI with Vertex AI's diverse evaluation services, including both computation-based and model-based methods.
- Implement best practices for LLM evaluation, to ensure robust and reliable model deployment in production environments.
Prerequisites
- Proficiency with Python on topics covered in the Crash Course on Python offered by Google.
- Prior experience with foundational machine learning concepts and building machine learning solutions on Google Cloud as covered in the Machine Learning on Google Cloud courses
Available languages
English, Deutsch, español (Latinoamérica), français, bahasa Indonesia, 日本語, 한국어, português (Brasil), 简体中文, and 繁體中文