Machine Learning in the Enterprise
Machine Learning in the Enterprise
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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing.
The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.
课程信息
目标
- Describe data management, governance, and preprocessing options.
- Identify when to use Vertex AutoML, BigQuery ML, and custom training.
- Implement Vertex Vizier Hyperparameter Tuning.
- Explain how to create batch and online predictions, setup model monitoring, and create pipelines using Vertex AI.
前提条件
Some familiarity with basic machine learning concepts
Basic proficiency with a scripting language; Python preferred
受众
- Data Analysts
- Data Engineers
- Data Scientists
- ML Engineers
- ML Software Engineers
支持的语言
English, español (Latinoamérica), 日本語, français, 한국어, and português (Brasil)
学完本课程后，我可以做些什么？
学完本课程后，您可以探索学习路线 中的其他内容或浏览学习目录
我能获得什么徽章？
学完一门课程后，您将获得结业徽章。徽章可在个人资料中供查看，还可在社交网络上分享。
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