Engenharia de atributos básica no Keras avaliações

M R. · Revisado há about 4 years

Mario R. · Revisado há about 4 years

Brandon G. · Revisado há about 4 years

Ang X. · Revisado há about 4 years

Sanjay B. · Revisado há about 4 years

Clive N. · Revisado há about 4 years

Sanjay B. · Revisado há about 4 years

Cheikh T. · Revisado há about 4 years

chhaya s. · Revisado há about 4 years

very difficult.

Steven S. · Revisado há about 4 years

Sergio Adriano L. · Revisado há about 4 years

Brenno M. · Revisado há about 4 years

Takashi D. · Revisado há about 4 years

Nicolo L. · Revisado há about 4 years

Corinna F. · Revisado há about 4 years

Sophie S. · Revisado há about 4 years

Guilherme A. · Revisado há about 4 years

Guilherme A. · Revisado há about 4 years

Sometimes methods for loading in data is confusing.

Tiego T. · Revisado há about 4 years

Xiaohui L. · Revisado há about 4 years

Mojtaba G. · Revisado há about 4 years

Finally got through the lab after a few attempts, the use of the min max function here, which relies on pandas functionality, is not intuitive. I would have preferred if we instead used a normalization layer which is native to tensorflow. Furthermore, setting random seeds so the work is reproducible/verifiable would be helpful in quantifying the model improvements and incorporating that in the notebook. The instructions for predictions on the test dataset weren't very clear to me. I think there's a missed opportunity here to do things like [(X, y)] = test_ds.take(1), model.predict(X), and likewise feature_layer(X) to help the student understand what's happening under the good. Thank you!

Pritam D. · Revisado há about 4 years

Samuel D. · Revisado há about 4 years

Adriana B. · Revisado há about 4 years

Ritish A. · Revisado há about 4 years