The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
Overview
The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.
Syllabus
- Introduction 0mins
- Get to Know Your Data: Improve Data through Exploratory Data Analysis 56mins
- Machine Learning in Practice 46mins
- Training AutoML Models Using Vertex AI 38mins
- BigQuery Machine Learning: Develop ML Models Where Your Data Lives 31mins
- Optimization 58mins
- Generalization and Sampling 28mins
- Summary 0mins
Taught by
Google Cloud