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.
Об этом курсе
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
- 5 stars68,88 %
- 4 stars24 %
- 3 stars4,44 %
- 2 stars1,51 %
- 1 star1,15 %
Лучшие отзывы о курсе SMART ANALYTICS, MACHINE LEARNING, AND AI ON GCP
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).
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.
Excellent course. Gets pretty advanced with developing ML pipelines with Kubernetes Engine, but otherwise very accessible.
Very good course to experience all the diverse offerings for ML on GCP.
Часто задаваемые вопросы
Можно ли ознакомиться с курсом до регистрации?
Что я получу, зарегистрировавшись на курс?
Когда я получу сертификат о прохождении курса?
Почему я не могу прослушать этот курс?
Остались вопросы? Посетите Центр поддержки учащихся.