Google Cloud の ML API 用にデータを準備: チャレンジラボ のレビュー

Vasudevan Mahesh · 3ヶ月前にレビュー済み

Benavides Cristopher · 3ヶ月前にレビュー済み

SURLA NAVEEN 25EU06R0167 - · 3ヶ月前にレビュー済み

Biswal Gourab · 3ヶ月前にレビュー済み

PUIN MOTAVITA DANIEL FELIPE · 3ヶ月前にレビュー済み

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.

Pearce Jacqueline · 3ヶ月前にレビュー済み

Biswal Gourab · 3ヶ月前にレビュー済み

Deka Tanuj · 3ヶ月前にレビュー済み

Hawaldar Sachin · 3ヶ月前にレビュー済み

Bal Mateusz · 3ヶ月前にレビュー済み

Kumar Rahul · 3ヶ月前にレビュー済み

Biswal Gourab · 3ヶ月前にレビュー済み

Devi Aarti · 3ヶ月前にレビュー済み

Vasudevan Mahesh · 3ヶ月前にレビュー済み

Kumar Gulshan · 3ヶ月前にレビュー済み

Biswal Gourab · 3ヶ月前にレビュー済み

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

Vaghela Nayan · 3ヶ月前にレビュー済み

Miscali Davide · 3ヶ月前にレビュー済み

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

Castro Morell Daniel · 3ヶ月前にレビュー済み

Nice !!!

Mulla Zinnoor · 3ヶ月前にレビュー済み

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.

Mishra Anshuman · 3ヶ月前にレビュー済み

Pamuru Induja · 3ヶ月前にレビュー済み

Ibañez Samuel · 3ヶ月前にレビュー済み

JAIN MANVI · 3ヶ月前にレビュー済み

GOOGLEUSER Akanksha · 3ヶ月前にレビュー済み