Prepare Data for ML APIs on Google Cloud: チャレンジラボ のレビュー

Gustavo Luis · 8ヶ月前にレビュー済み

NURHIDAYAT AZIZ · 8ヶ月前にレビュー済み

Anchewar Pooja · 8ヶ月前にレビュー済み

Duy Huỳnh Nhật · 8ヶ月前にレビュー済み

Virgilio Domenic · 8ヶ月前にレビュー済み

Gweje Nicholson · 8ヶ月前にレビュー済み

Huân Lê Đăng · 8ヶ月前にレビュー済み

Long Phạm Hoàng · 8ヶ月前にレビュー済み

Akula Divya sri · 8ヶ月前にレビュー済み

Kour Jasleen · 8ヶ月前にレビュー済み

Anchewar Pooja · 8ヶ月前にレビュー済み

Xavier Barboza Alef · 8ヶ月前にレビュー済み

GUEYE Fatou Diakhate · 8ヶ月前にレビュー済み

GOOGLEUSER wagner Nogueira · 8ヶ月前にレビュー済み

Ashmitha Panuganti · 8ヶ月前にレビュー済み

Zhen Bin Chong · 8ヶ月前にレビュー済み

Maldonado Fernández Jesús · 8ヶ月前にレビュー済み

Hire Mayuri Raosaheb · 8ヶ月前にレビュー済み

Please note that the output for files (metadata) should be application/json in the GCS buckets for tasks 3 and 4. Without that the check fails

Gulin Pavel · 8ヶ月前にレビュー済み

Zhen Bin Chong · 8ヶ月前にレビュー済み

good lab

Thoại Lê Viết · 8ヶ月前にレビュー済み

Steps 3 and 4 confused me as compared to the referenced labs. Was I to use the console or the shell? I tried both, but in the end, I had to juggle things around. I found it hard to access the storage bucket from the shell. Whereas in the referenced qwik start labs, the end-results are saved as ".result" files, the challenge labs expect to see JSON files. What am I missing here? For example, with the natural language task, how do I get the result created within the bucket? How do I modify the final API call? gcloud ml language analyze-entities --content="example_text" > result.json What do I change the "result.json" into? How do I point to the GS bucket? Cheers :)

Martinis Chris · 8ヶ月前にレビュー済み

Khoa Phan Trần Anh · 8ヶ月前にレビュー済み

Nguyễn Duy Hoàn · 8ヶ月前にレビュー済み

excellent lab, really made it difficult for me.

N Vineeth · 8ヶ月前にレビュー済み