This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators.Read more.
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The techniques and tools covered in Production Machine Learning Systems are most similar to the requirements found in Data Scientist job advertisements.
