Hi @Prasad_Sonar,
I checked your notebook. Here’s what I’ve found.
-
In C2W2 Assignment:
Exercise 1 is missing#grader-required-cell
at several exercises (1, 2, 3, 4, 5).
At exercise 5, you don’t need to import every module again. Please don’t add any new cells and only edit within### START CODE HERE
At exercise 6, removealways_return_num_quantiles=False
as that option doesn’t exist in tft.bucketize(). For traffic_volume, there’s no such_fill_in_missing
module. You can use normal tf.cast(). The outputs also have IndexError and TypeError. Please double checktft.mean(tf.cast(input, dtype))
For exercise 7, I believe you accidentally created some new cells and forget to fill out exercise 7. There’s also an extra cell with# grade-up-to-here
. This may be why your assignment is not getting graded properly. -
In C2W3 Assignment:
Missing#grader-required-cell
at several exercises. There are also extra cells and there’s a duplicate metadata### START CODE HERE ###
Also, you usedImporterNode
instead of the suggested functionImportSchemaGen
.
The variable ofuser_schema_importer.outputs
is incorrect. The default should have been
as it’s written for in the notebook
context.show(user_schema_importer.outputs['schema'])
In Exercise 8, when stats_options.schema is set, it will be used instead of the schema
channel input. Since you add both schema and stats_options, an error will be raised. See more. In excercise 11, you used the original schema artifact instead of the curated schema (user_schema_importer)
Follow these steps to grab the fresh notebook. Only put your solutions in between the ### START CODE HERE
and ### END CODE HERE
code comments, and also refrain from adding any new cells.
Please be mindful that if you delete/add/edit any cell that has this # tag during your work, you may mistakenly delete important metadata that will be used for the submission and grading process at the end.