Prepara i dati per le API ML su Google Cloud: Challenge Lab recensioni

Mahesh V. · Recensione inserita 3 mesi fa

Cristopher B. · Recensione inserita 3 mesi fa

25EU06R0167 - S. · Recensione inserita 3 mesi fa

Gourab B. · Recensione inserita 3 mesi fa

DANIEL FELIPE P. · Recensione inserita 3 mesi fa

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. · Recensione inserita 3 mesi fa

Gourab B. · Recensione inserita 3 mesi fa

Tanuj D. · Recensione inserita 3 mesi fa

Sachin H. · Recensione inserita 3 mesi fa

Mateusz B. · Recensione inserita 3 mesi fa

Rahul K. · Recensione inserita 3 mesi fa

Gourab B. · Recensione inserita 3 mesi fa

Aarti D. · Recensione inserita 3 mesi fa

Mahesh V. · Recensione inserita 3 mesi fa

Gulshan K. · Recensione inserita 3 mesi fa

Gourab B. · Recensione inserita 3 mesi fa

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

Nayan V. · Recensione inserita 3 mesi fa

Davide M. · Recensione inserita 3 mesi fa

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

Daniel C. · Recensione inserita 3 mesi fa

Nice !!!

Zinnoor M. · Recensione inserita 3 mesi fa

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. · Recensione inserita 3 mesi fa

Induja P. · Recensione inserita 3 mesi fa

Samuel I. · Recensione inserita 3 mesi fa

MANVI J. · Recensione inserita 3 mesi fa

Akanksha G. · Recensione inserita 3 mesi fa