Performing Basic Feature Engineering in Keras Reviews

Cheikh T. · Reviewed over 3 years ago

chhaya s. · Reviewed over 3 years ago

very difficult.

Steven S. · Reviewed over 3 years ago

Sergio Adriano L. · Reviewed over 3 years ago

Brenno M. · Reviewed over 3 years ago

Takashi D. · Reviewed over 3 years ago

Nicolo L. · Reviewed over 3 years ago

Corinna F. · Reviewed over 3 years ago

Sophie S. · Reviewed over 3 years ago

Guilherme A. · Reviewed over 3 years ago

Guilherme A. · Reviewed over 3 years ago

Sometimes methods for loading in data is confusing.

Tiego T. · Reviewed over 3 years ago

Xiaohui L. · Reviewed over 3 years ago

Mojtaba G. · Reviewed over 3 years ago

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. · Reviewed over 3 years ago

Samuel D. · Reviewed over 3 years ago

Adriana B. · Reviewed over 3 years ago

Ritish A. · Reviewed over 3 years ago

Anna Elisabetta Z. · Reviewed over 3 years ago

Snehashis J. · Reviewed over 3 years ago

Mohammad A. · Reviewed over 3 years ago

Mark M. · Reviewed over 3 years ago

Dany T. · Reviewed over 3 years ago

Victor P. · Reviewed over 3 years ago

Supratim B. · Reviewed over 3 years ago