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 Platform 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 AI Platform Notebooks and BigQuery Machine Learning. 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 Platform using QwikLabs.
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来自SMART ANALYTICS, MACHINE LEARNING, AND AI ON GCP的热门评论
I couldn't complete the Kubeflow lab due to issues that I encountered setting it up. Overall, the course has given me a good understanding of Machine Learning model creation options available on GCP
It was a good decision to do this course as i learn and practiced lot in GCP. Thank you the team for amazing support guidance and instructions. Course content and material was appreciated. Thanks.
Very good ML course to introduce students with Google Cloud machine learning capabilities. Maybe there should be a lab for AutoML (after video lessons), as it exists on Qwiklab platform.
Content was fun and exciting but some exercises/graded labs inside this course are very unclear with the instructions and also took a long time to finish (model training).
该课程是 Coursera 上提供的为数不多的课程之一，目前只对已购买课程或已获得助学金的学生开放。