关于“Classifying Images of Clouds in the Cloud with AutoML Vision”的评价
41916 条评价
Anderson M. · 已于 over 3 years前审核
Dipsikha T. · 已于 over 3 years前审核
Chandra K. · 已于 over 3 years前审核
Cristian C. · 已于 over 3 years前审核
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Harindha F. · 已于 over 3 years前审核
Joe W. · 已于 over 3 years前审核
Aashis K. · 已于 over 3 years前审核
great understandable presentation
chollangi c. · 已于 over 3 years前审核
Riccardo S. · 已于 over 3 years前审核
sangavi k. · 已于 over 3 years前审核
Yi L. · 已于 over 3 years前审核
Cheng L. · 已于 over 3 years前审核
Yogesh J. · 已于 over 3 years前审核
賢司 塩. · 已于 over 3 years前审核
Laxman K. · 已于 over 3 years前审核
Henry L. · 已于 over 3 years前审核
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Leo B. · 已于 over 3 years前审核
Aditi S. · 已于 over 3 years前审核
Rahul J. · 已于 over 3 years前审核
Definitely the worst lab so far. The instructions are out of date - e.g. CSV-based image import seems to require a header row, absent in the original data.csv; it succeeded only after I've added the labels; visiting web UI of GCS is confusing as it serves no purpose - CLI is used to copy all the files *and to list them*, so visit to UI is redundant and makes the student wonder if they've missed someting. I feel like I've learned nothing, it was just copying files from one bucket to another and clicking some buttons with default settings... Now for the constructive part: how about providing a pre-trained model to copy to student's account instead of telling them to "see the screenshots"? How about changing the dataset used for training (image sizes range from 50 KB to whopping 9 MB!) - if you're just showcasing the tool, maybe something smaller/simpler would suffice? I'm no expert in ML, but I suppose that teaching the model to recognize items on 64x64 px icons would be much faster. Or maybe provide 2 or 3 pre-trained models with different quality of input images to show the differences? Please review the lab and update the instructions, in its current form it's a waste of time and resources.
Andrzej G. · 已于 over 3 years前审核
Vinayak H. · 已于 over 3 years前审核
José T. · 已于 over 3 years前审核
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