Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
Overview
Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
Syllabus
- Introduction 1min
- Introduction to Analytics and AI 8mins
- Prebuilt ML Model APIs for Unstructured Data 8mins
- Big Data Analytics with Notebooks 7mins
- Production ML Pipelines 8mins
- Custom Model Building with SQL in BigQuery ML 12mins
- Custom Model Building with Vertex AI AutoML 24mins
- Summary 0mins
- Course Resources 0mins
Taught by
Google Cloud
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