Preparação de dados para APIs de ML no Google Cloud: laboratório com desafio avaliações

Mahesh V. · Revisado há 3 months

Cristopher B. · Revisado há 3 months

25EU06R0167 - S. · Revisado há 3 months

Gourab B. · Revisado há 3 months

DANIEL FELIPE P. · Revisado há 3 months

Generally good but the requirement for validating the API calls was unclear. I outputted the result directly to a .result file on my filesystem and uploaded that with gsutil, which it didn't accept (although this is a perfectly valid Linux command). It only validated it as correct when I piped the output to a .json file, and then did the rename at the gsutil upload stage. This is poor validation since both ways are correct.

Jacqueline P. · Revisado há 3 months

Gourab B. · Revisado há 3 months

Tanuj D. · Revisado há 3 months

Sachin H. · Revisado há 3 months

Mateusz B. · Revisado há 3 months

Rahul K. · Revisado há 3 months

Gourab B. · Revisado há 3 months

Aarti D. · Revisado há 3 months

Mahesh V. · Revisado há 3 months

Gulshan K. · Revisado há 3 months

Gourab B. · Revisado há 3 months

i got problem that my 3rd task not showing completed even after i completed

Nayan V. · Revisado há 3 months

Davide M. · Revisado há 3 months

In instructions (dataproc) indication was run the job in a N2 cluster, but impossible to choose that option (only N4 available)

Daniel C. · Revisado há 3 months

Nice !!!

Zinnoor M. · Revisado há 3 months

Data allocation for ML API are discretized with parallel and scalable function for a running Dataflow template region enabled in a Cloud Shell region with its compatible Cloud Storage Bucket instance.

Anshuman M. · Revisado há 3 months

Induja P. · Revisado há 3 months

Samuel I. · Revisado há 3 months

MANVI J. · Revisado há 3 months

Akanksha G. · Revisado há 3 months