Smart Analytics, Machine Learning, and AI on Google Cloud
Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. 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 using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs. This is the fourth course of the Data Engineering on Google Cloud series.</p>
What you'll learn
Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. 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 using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs.
This is the fourth course of the Data Engineering on Google Cloud series.
Table of contents
- Module introduction 1m
- BigQuery ML for Quick Model Building 4m
- Supported models 7m
- Lab Intro: Predict Bike Trip Duration with a Regression Model in BigQuery ML 0m
- Lab: Predict Bike Trip Duration with a Regression Model in BQML 2.5 0m
- Lab Intro: Movie Recommendations in BigQuery ML 0m
- Lab: Movie Recommendations in BigQuery ML 2.5 0m
- Summary 0m
