关于“通过 BigQuery ML 创建机器学习模型：实验室挑战赛”的评价

Lorenzo S. · 已于 over 1 year前审核

Iker A. · 已于 over 1 year前审核

Manuel Angel A. · 已于 over 1 year前审核

Mehdi M. · 已于 over 1 year前审核

vivek k. · 已于 over 1 year前审核

Amanda B. · 已于 over 1 year前审核

Sijo Jose C. · 已于 over 1 year前审核

buggy

Joseph J. · 已于 over 1 year前审核

Susana D. · 已于 over 1 year前审核

Shivaji D. · 已于 over 1 year前审核

Mehdi M. · 已于 over 1 year前审核

Sivakumar V. · 已于 over 1 year前审核

krishna k. · 已于 over 1 year前审核

Done...

Miguel M. · 已于 over 1 year前审核

Krishna K. · 已于 over 1 year前审核

Krishna K. · 已于 over 1 year前审核

Travis H. · 已于 over 1 year前审核

Mehdi M. · 已于 over 1 year前审核

Alexander D. · 已于 over 1 year前审核

Andrew G. · 已于 over 1 year前审核

Unclear language. Also the instruction itself. Lack the details. I've lost several hours on trying to guess what is wrong and FAILED. Misleading parts of the instructions: - "Also you have to specify the model type as binary logistic regression... Use the model type as linear regression model" - "create a dataset with the dataset ID 'bq_dataset' ... Create a model ... in the precreated dataset 'bqml_dataset'"... with each attempt I was trying to create my model in each of these databases... It is not said which day partitions should be used for training when there are lots of them. And for evaluation. Evaluation by users, not explicitly said which column it is. userId and visitorId columns are always NULL. Google analytics is not known to every user, and it is not mentioned as a prerequisite for this exercise. That's why it's important to clearly describe the columns to be used. Or maybe the error messages could be more helpful. Now they say "create a model... in dataset"... and it's created but the check fails. Sometimes checking progress shows failure for some time, and after some time returns success without changing anything.

Wojciech C. · 已于 over 1 year前审核

Aldhitya P. · 已于 over 1 year前审核

task 4 always give me errors. Needs further instructions even though I have an output

Nikos L. · 已于 over 1 year前审核

Sometimes checking progress shows failure for some time, and after some time returns success without changing anything. You often ask to create a dataset e.g. 'bq_dataset' and then ask to create a model in different but similar dataset e.g. 'bqml_dataset'. It's misleading. Often it's not directly shown where the data is located (Google analytics tables) or not said which day partitions should be used for training when there are lots of them. This task assumes good knowledge of Google Analytics, but it's not introduced earlier... and it's not fair in my opinion.

Wojciech C. · 已于 over 1 year前审核

It was good but a bit repetived, i would like to create a model in a new dataset, maybe something simple like a iris datset or the housing dataset and leet the user chose his features

Antonio O. · 已于 over 1 year前审核