Prepare Data for ML APIs on Google Cloud: Challenge Lab recensioni

Amaludin I. · Recensione inserita 8 mesi fa

Luis G. · Recensione inserita 8 mesi fa

AZIZ N. · Recensione inserita 8 mesi fa

Pooja A. · Recensione inserita 8 mesi fa

Huỳnh Nhật D. · Recensione inserita 8 mesi fa

Domenic V. · Recensione inserita 8 mesi fa

Nicholson G. · Recensione inserita 8 mesi fa

Lê Đăng H. · Recensione inserita 8 mesi fa

Phạm Hoàng L. · Recensione inserita 8 mesi fa

Divya sri A. · Recensione inserita 8 mesi fa

Jasleen K. · Recensione inserita 8 mesi fa

Pooja A. · Recensione inserita 8 mesi fa

Alef X. · Recensione inserita 8 mesi fa

Fatou Diakhate G. · Recensione inserita 8 mesi fa

wagner Nogueira G. · Recensione inserita 8 mesi fa

Panuganti A. · Recensione inserita 8 mesi fa

Chong Z. · Recensione inserita 8 mesi fa

Jesús M. · Recensione inserita 8 mesi fa

Mayuri Raosaheb H. · Recensione inserita 8 mesi fa

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

Pavel G. · Recensione inserita 8 mesi fa

Chong Z. · Recensione inserita 8 mesi fa

good lab

Lê Viết T. · Recensione inserita 8 mesi fa

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 :)

Chris M. · Recensione inserita 8 mesi fa

Phan Trần Anh K. · Recensione inserita 8 mesi fa

Duy Hoàn N. · Recensione inserita 8 mesi fa