Member since 2024
Model Armor：保護您部署的 AI 應用程式
Earned Mar 15, 2026 EDT
Machine Learning Operations (MLOps): Getting Started
Earned Jul 9, 2024 EDT
[Depricated] Build, Train and Deploy ML Models with Keras on Google Cloud
Earned Jul 4, 2024 EDT
Google Cloud 的 AI 和機器學習服務簡介
Earned Jul 1, 2024 EDT
本課程將複習 Model Armor 的基本安全功能，讓您具備使用這項服務的能力。您將瞭解 LLM 的相關安全風險，以及 Model Armor 如何保護 AI 應用程式。
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
本課程介紹 Google Cloud 的 AI 和機器學習 (ML) 功能，著重說明如何開發生成式和預測式 AI 專案。我們也會探討「從資料到 AI」整個生命週期都適用的技術、產品和工具，並透過互動式練習，協助資料科學家、AI 開發人員和機器學習工程師精進專業知識。