关于“Machine Learning with TensorFlow and Vertex AI”的评价

评论

Jad Z. · 评论over 4 years之前

more time to investigate the code would be nice

Dominik L. · 评论over 4 years之前

Very Tough one

Owais A. · 评论over 4 years之前

Andrew M. · 评论over 4 years之前

In Create minimal training and test datasets, repeated instruction and code chunk could be removed: Create the training data... rm full.csv` In Create a TensorFlow experimental framework in Python, the training model didn't execute correctly since my output was different from the expected: INFO:tensorflow:Saving dict for global step 200: accuracy = 0.89453167, accuracy_baseline = 0.72878134, auc = 0.88293874, auc_precision_recall = 0.946697, average_loss = 0.5809859, global_step = 200, label/mean = 0.72878134, loss = 290.5801, precision = 0.90075845, prediction/mean = 0.7678837, recall = 0.9611797, rmse = 0.3024143 To be: tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [string_input_producer requires a non-null input tensor] [[{{node input_producer/Assert/Assert}}]] However, the job appears to execute seamlessly and with lots of Warning (148) and Error (32).

Moria W. · 评论over 4 years之前

Trivikram M. · 评论over 4 years之前

Sunit M. · 评论over 4 years之前

Ran out of time on the first try. Had to do it again, but even then, needed to blaze through it to get it all done in time. IMO, this lab would be better if it allowed for an hour and a half or even 2 hours, to give time to really understand the code and what is happening

Joe R. · 评论over 4 years之前

rozan w. · 评论over 4 years之前

Aitor M. · 评论over 4 years之前

Saloua L. · 评论over 4 years之前

rozan w. · 评论over 4 years之前

Ahmad E. · 评论over 4 years之前

1

SEONJU L. · 评论over 4 years之前

SEONJU L. · 评论over 4 years之前

Ran out of time.

Joe R. · 评论over 4 years之前

Good

Eli K. · 评论over 4 years之前

not enough time.

Rania B. · 评论over 4 years之前

Imen M. · 评论over 4 years之前

NIWAT R. · 评论over 4 years之前

Walter W. · 评论over 4 years之前

salman K. · 评论over 4 years之前

salman K. · 评论over 4 years之前

Pedro Paulo M. · 评论over 4 years之前

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