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Learner Reviews & Feedback for Production Machine Learning Systems by Google Cloud
1,020 ratings
About the Course
In this course, we dive into the components and best practices of building high-performing ML systems in production environments. We cover some of the most common considerations behind building these systems, e.g. static training, dynamic training, static inference, dynamic inference, distributed TensorFlow, and TPUs. This course is devoted to exploring the characteristics that make for a good ML system beyond its ability to make good predictions.
Top reviews
BA
Sep 22, 2020
Unlike pure technical courses, this one specially packs you with knowledge that you may find yourself face to. The course is really well designed and the content is crystal clear, just Awesome !
AJ
May 16, 2021
Excellent overview of designing real-world ML systems. Some of the labs are daunting, but the emphasis is showing you what can be achieved, rather than achieving mastery within the course.
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