关于“在 Google Cloud 為機器學習 API 準備資料：挑戰實驗室”的评价

Many different tasks

Kalman T. · 评论4 months之前

Juuso T. · 评论4 months之前

RIJAL M. · 评论4 months之前

Mallikarjun R. · 评论4 months之前

Dinesh V. · 评论4 months之前

Ashique A. · 评论4 months之前

Venkata Sai Karthik N. · 评论4 months之前

Venkata Sai Karthik N. · 评论4 months之前

Dilson B. · 评论4 months之前

PREETHI ROYAL A. · 评论4 months之前

Venkata Sai Karthik N. · 评论4 months之前

Venkata Sai Karthik N. · 评论4 months之前

Gissel Monserrath C. · 评论4 months之前

SIRAJ AHAMMAD C. · 评论4 months之前

Srinadh C. · 评论4 months之前

Ashley L. · 评论4 months之前

lina paola a. · 评论4 months之前

Ashley L. · 评论4 months之前

Ashley L. · 评论4 months之前

Ty S. · 评论4 months之前

A lot!

Rose C. · 评论4 months之前

Couldn't be less satisfied, I completed the two ending tasks, but the platform didn't recognize the completion and made a total wast of my time and credits, what makes me more angry is the fact that this challenge requires 5 credits, what is going to demand of me a substantial drain of credits that I would otherwise use in other labs, to to try this !@#$% lab again and try to guess what this !@#$% requires me to do. I followed all the instructions to the letter and yet...

Adriano C. · 评论4 months之前

Saving the initial result from the Google Cloud Speech-to-Text API and Cloud Natural Language API directly into the Cloud Shell file system saves it as type 'application/octet', I recall. For some reason, if you then directly upload this to the Cloud Storage bucket using `gcloud storage cp XXXX.result gs://BUCKET_NAME/XXXX.result`, the lab cannot seem to read the file and acknowledge the step completion. It might be good to have a warning that the output must first be output into a JSON file in the Cloud Shell filesystem, or that the desired result should be in the bucket as `application/json`.

Tuany V. · 评论4 months之前

Nestor Stiven P. · 评论4 months之前

Ashley L. · 评论4 months之前