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

Amaludin I. · Reviewed 8 months ago

Luis G. · Reviewed 8 months ago

AZIZ N. · Reviewed 8 months ago

Pooja A. · Reviewed 8 months ago

Huỳnh Nhật D. · Reviewed 8 months ago

Domenic V. · Reviewed 8 months ago

Nicholson G. · Reviewed 8 months ago

Lê Đăng H. · Reviewed 8 months ago

Phạm Hoàng L. · Reviewed 8 months ago

Divya sri A. · Reviewed 8 months ago

Jasleen K. · Reviewed 8 months ago

Pooja A. · Reviewed 8 months ago

Alef X. · Reviewed 8 months ago

Fatou Diakhate G. · Reviewed 8 months ago

wagner Nogueira G. · Reviewed 8 months ago

Panuganti A. · Reviewed 8 months ago

Chong Z. · Reviewed 8 months ago

Jesús M. · Reviewed 8 months ago

Mayuri Raosaheb H. · Reviewed 8 months ago

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. · Reviewed 8 months ago

Chong Z. · Reviewed 8 months ago

good lab

Lê Viết T. · Reviewed 8 months ago

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. · Reviewed 8 months ago

Phan Trần Anh K. · Reviewed 8 months ago

Duy Hoàn N. · Reviewed 8 months ago