16
Machine Learning Operations (MLOps) with Vertex AI: Model Evaluation
16
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.
과정 정보
목표
- 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.
기본 요건
- 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
사용할 수 있는 언어
English
과정을 완료한 후에는 어떻게 해야 하나요?
과정을 완료한 후 학습 과정 에서 다른 콘텐츠를 살펴보거나 학습 카탈로그 를 둘러보면 됩니다.
어떤 배지를 획득할 수 있나요?
과정을 완료하면 이수 배지가 주어집니다. 배지는 프로필에 표시되며 사회 연결망에서 공유할 수 있습니다.
Google의 주문형 파트너에서 제공하는 과정에 관심이 있으신가요?
Coursera 및 Pluralsight 에서 Google Cloud 콘텐츠를 살펴보세요.
강사 주도 강좌를 선호하시나요?