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 Vertex AI. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs.
About this Course
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.
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TOP REVIEWS FROM SMART ANALYTICS, MACHINE LEARNING, AND AI ON GCP
This course helped me to do smart analytics, and in my current job I was able to apply Machine Learning easily on GCP, and I helped my team to the AI platform like experts.
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.
Amazing to be part of this great learning Journey!! I am learning concepts and strong fundamentals to build a good foundation.
Great Big Picture about ML options on GCP, with good highlighting to main advantages and differences for each option.
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