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Distributed Machine Learning with Google Cloud ML

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3388 Reviews

Youssef A. · Reviewed about 2 hours ago

Selin Doga O. · Reviewed about 2 hours ago

Göktuğ Y. · Reviewed about 2 hours ago

fouad k. · Reviewed about 3 hours ago

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Orkun Mahir K. · Reviewed about 3 hours ago

Muhammet Mustafa D. · Reviewed about 3 hours ago

Nuran T. · Reviewed 10 days ago

ZICHUANG X. · Reviewed 11 days ago

sivsov h. · Reviewed 11 days ago

Federico L. · Reviewed 11 days ago

oussema c. · Reviewed 11 days ago

Raul R. · Reviewed 11 days ago

sivsov h. · Reviewed 12 days ago

Meiliany P. · Reviewed 12 days ago

Couple of issues: In several places ml engine is still used instead of ai platform, and since the introduction of global students will need to set up a region in order for the lab to finish. The point grader will only accept us-central1, so I had to manually create a model resource and deploy it there for us-central1, in order for the grader to work. By default the commands in the tutorial created a resource in global for me.

Jeffrey L. · Reviewed 12 days ago

would be nice if both python version and tensorflow updated

Hanati T. · Reviewed 12 days ago

ML Model command on the last "Deploying" section should be modified, not to provide region details. Otherwise, ML model is created with the wrong endpoint and the next command for the V1 creation fails. Please, update.

Laziz T. · Reviewed 12 days ago

Alwin J. · Reviewed 13 days ago

Matthew D. · Reviewed 13 days ago

Hola M. · Reviewed 14 days ago

khalil a. · Reviewed 14 days ago

Milos B. · Reviewed 14 days ago

Kailash T. · Reviewed 15 days ago

There is a problem in last stage, Deployment of model script is not working due to region is not correctly specified.

Cem G. · Reviewed 15 days ago

The last step did not register for points, even though it all worked and the python script returned a response from the cloud endpoint.

Cory R. · Reviewed 16 days ago