Advanced Visualizations with TensorFlow Data Validation Reviews

Siddhesh N. · Reviewed 2 yıldan fazla ago

Dave S. · Reviewed 2 yıldan fazla ago

kishore k. · Reviewed 2 yıldan fazla ago

done

Kishore K. · Reviewed 2 yıldan fazla ago

Rupesh P. · Reviewed 2 yıldan fazla ago

julien P. · Reviewed 2 yıldan fazla ago

Aljon P. · Reviewed 2 yıldan fazla ago

Awesome!

Luis Ángel M. · Reviewed 2 yıldan fazla ago

Manuel P. · Reviewed 2 yıldan fazla ago

I had to complete the lab locally due to the course being out of date

Matthew V. · Reviewed 2 yıldan fazla ago

dailin m. · Reviewed 2 yıldan fazla ago

Fahad A. · Reviewed 2 yıldan fazla ago

Pritam B. · Reviewed 2 yıldan fazla ago

great

Snehal C. · Reviewed 2 yıldan fazla ago

Hugo M. · Reviewed 2 yıldan fazla ago

Nirmal R. · Reviewed 2 yıldan fazla ago

Xiaofeng X. · Reviewed 2 yıldan fazla ago

Rana A. · Reviewed 2 yıldan fazla ago

Srikeerti V. · Reviewed 2 yıldan fazla ago

Omar E. · Reviewed 2 yıldan fazla ago

Laszlo S. · Reviewed 2 yıldan fazla 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 2 yıldan fazla ago

Abdul Q. · Reviewed 2 yıldan fazla ago

maziyar a. · Reviewed 2 yıldan fazla ago