Advanced Visualizations with TensorFlow Data Validation Reviews

Dave S. · Reviewed больше 2 лет ago

kishore k. · Reviewed больше 2 лет ago

done

Kishore K. · Reviewed больше 2 лет ago

Rupesh P. · Reviewed больше 2 лет ago

julien P. · Reviewed больше 2 лет ago

Aljon P. · Reviewed больше 2 лет ago

Awesome!

Luis Ángel M. · Reviewed больше 2 лет ago

Manuel P. · Reviewed больше 2 лет ago

I had to complete the lab locally due to the course being out of date

Matthew V. · Reviewed больше 2 лет ago

dailin m. · Reviewed больше 2 лет ago

Fahad A. · Reviewed больше 2 лет ago

Pritam B. · Reviewed больше 2 лет ago

great

Snehal C. · Reviewed больше 2 лет ago

Hugo M. · Reviewed больше 2 лет ago

Nirmal R. · Reviewed больше 2 лет ago

Xiaofeng X. · Reviewed больше 2 лет ago

Rana A. · Reviewed больше 2 лет ago

Srikeerti V. · Reviewed больше 2 лет ago

Omar E. · Reviewed больше 2 лет ago

Laszlo S. · Reviewed больше 2 лет ago

This comment in the notebook is not consistent with the "serving data": "We also have an INT value in our trip seconds, where our schema expected a FLOAT. By making us aware of that difference, TFDV helps uncover inconsistencies in the way the data is generated for training and serving. It's very easy to be unaware of problems like that until model performance suffers, sometimes catastrophically. It may or may not be a significant issue, but in any case this should be cause for further investigation. In this case, we can safely convert INT values to FLOATs, so we want to tell TFDV to use our schema to infer the type. Let's do that now." Actually no anomly is detected for "trip seconds" feature.

Giovanna S. · Reviewed больше 2 лет ago

Abdul Q. · Reviewed больше 2 лет ago

maziyar a. · Reviewed больше 2 лет ago

Wagner S. · Reviewed больше 2 лет ago

Daniel L. · Reviewed больше 2 лет ago