This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.
Overview
This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.
Syllabus
- Introduction to Course and Series 3mins
- What It Means to be AI-First 35mins
- How Google Does ML 30mins
- Machine Learning Development with Vertex AI 40mins
- Machine Learning Development with Vertex Notebooks 19mins
- Best Practices for Implementing Machine Learning on Vertex AI 11mins
- Responsible AI Development 33mins
- Summary 0mins
Taught by
Google Cloud