关于“運用 BigQuery ML 建立機器學習模型:挑戰實驗室”的评价
评论
Very disappointing. 1) The dataset is not clearly specified, the features neither (is the goal to check per unique visitor or per session?) 2) in the assignment, two contradicting instructions are given: "Also you have to specify the model type as binary logistic regression" and 2 lines below "Use the model type as linear regression model" - the second doesn't make sense for binary classification (will or won't buy). 3) No specification on how to deal with train-validation split; some labs have the split, some don't, it's ambiguous 4) even after trying all combinations (even with the linear regression, i.e. fitting the number of transactions as if it were float) the result gets NOT verified by the module. I got the data and trained a model myself separated from GCP and got THE SAME results as here, so obviously the model is well trained. Sad work out there, sorry.
Darina L. · 评论about 1 year之前
João T. · 评论about 1 year之前
krishna b. · 评论about 1 year之前
Pushpendra Y. · 评论about 1 year之前
Takahide M. · 评论about 1 year之前
Rajeswari P. · 评论about 1 year之前
Girish K. · 评论about 1 year之前
Denise T. · 评论about 1 year之前
Aditya S. · 评论about 1 year之前
Great
Pramod K. · 评论about 1 year之前
Asif M. · 评论about 1 year之前
It is important to make the instruction clearer stating that the student is to use already trained models and not to train another subscriber_type model. It can be confusing
GALINA K. · 评论about 1 year之前
Fredrick Barasa O. · 评论about 1 year之前
Changming C. · 评论about 1 year之前
Smita W. · 评论about 1 year之前
ok
Dipak V. · 评论about 1 year之前
Mariyam Ansar K. · 评论about 1 year之前
Gaurav M. · 评论about 1 year之前
Allen Y. · 评论about 1 year之前
Learning and Learning lots of learning
prateek G. · 评论about 1 year之前
Manish A. · 评论about 1 year之前
ラボの成功判定が問題文だけでは再現できないレベルに複雑すぎて、チャットサポートなしではクリア不可能
Ryo W. · 评论about 1 year之前
Chyn Chwen H. · 评论about 1 year之前
Marcelo V. · 评论about 1 year之前
The instruction in the last task is not clear, so it is impossible to understand what is being returned wrongly.
GALINA K. · 评论about 1 year之前
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