关于“ML on GCP [v1.0] - C4 - Improving model accuracy with new features”的评价

Could ask for estimation differences given changes in data. How including a new feature or adjusting its rang affects the model.

Julio M. · 已于 almost 8 years前审核

Average level. Not google level lab.

Jitender S. · 已于 almost 8 years前审核

Could ask for estimation differences given changes in data. How including a new feature or adjusting its rang affects the model.

Julio M. · 已于 almost 8 years前审核

Azadeh A. · 已于 almost 8 years前审核

Javier P. · 已于 almost 8 years前审核

Christian N. · 已于 almost 8 years前审核

Cabot N. · 已于 almost 8 years前审核

吳品曄 吳. · 已于 almost 8 years前审核

Some explanation of output would have been useful including comparison to loss found on earlier models.

Jon B. · 已于 almost 8 years前审核

Jiaming K. · 已于 almost 8 years前审核

Jeff L. · 已于 almost 8 years前审核

Min L. · 已于 almost 8 years前审核

Daniel F. · 已于 almost 8 years前审核

LTI S. · 已于 almost 8 years前审核

Enrique P. · 已于 almost 8 years前审核

Jamieson S. · 已于 almost 8 years前审核

Matt F. · 已于 almost 8 years前审核

Mario Y. · 已于 almost 8 years前审核

Ezra E. · 已于 almost 8 years前审核

I would have enjoyed a prediction. But I'm sort of getting used to having the summary during the following lab solution. Looks like average loss for eval data is a reasonalbe measure of relative training effectiveness for different features.

Charlie M. · 已于 almost 8 years前审核

I would have enjoyed a summary. But I'm sort of getting used to having the sumary during the following lab solution.

Charlie M. · 已于 almost 8 years前审核

Michael B. · 已于 almost 8 years前审核

Artan R. · 已于 almost 8 years前审核

LEE S. · 已于 almost 8 years前审核

Jeffrey S. · 已于 almost 8 years前审核