Parameterized pipeline runs in MLOps - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to pass a parameter named 'learning_rate' with value 0.01 to the pipeline run.

MLOps

pipeline_run = pipeline.run(parameters={"learning_rate": [1])

Drag options to blanks, or click blank then click option'

A0.1

B0.01

C1

D"0.01"

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the learning rate as a string instead of a float.

Using an incorrect value like 0.1.

The parameter 'learning_rate' should be passed as a float 0.01, not as a string or other value.

2fill in blank

medium

Complete the code to retrieve the parameter 'batch_size' from the pipeline run's parameters dictionary.

MLOps

batch_size = pipeline_run.parameters.get([1], 32)

Drag options to blanks, or click blank then click option'

A"batch_size"

B"batch"

Cbatch_size

D"size"

Attempts:

3 left

💡 Hint

Common Mistakes

Using a wrong key string like 'batch' or 'size'.

Using the variable name without quotes.

The key to retrieve the batch size parameter is the string 'batch_size'.

3fill in blank

hard

Fix the error in the code to correctly pass multiple parameters to the pipeline run.

MLOps

pipeline_run = pipeline.run(parameters=[1])

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A"epochs=10, lr=0.001"

B["epochs", 10, "lr", 0.001]

C("epochs", 10, "lr", 0.001)

D{"epochs": 10, "lr": 0.001}

Attempts:

3 left

💡 Hint

Common Mistakes

Passing parameters as a list or tuple instead of a dictionary.

Passing parameters as a string.

Parameters must be passed as a dictionary with keys and values, not as a list, tuple, or string.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that filters parameters with values greater than 0.5.

MLOps

filtered_params = {k: v for k, v in pipeline_run.parameters.items() if v [1] [2]

Drag options to blanks, or click blank then click option'

A>

B0.5

C<

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Using less than operator instead of greater than.

Using wrong threshold values.

The condition filters parameters where the value is greater than 0.5 using > and 0.5.

5fill in blank

hard

Fill all three blanks to create a dictionary of parameters where keys are uppercase and values are strings.

MLOps

param_strs = [1]: str([2]) for [3], v in pipeline_run.parameters.items()

Drag options to blanks, or click blank then click option'

Ak.upper()

Bv

Ck

Dv.upper()

Attempts:

3 left

💡 Hint

Common Mistakes

Using v.upper() which is invalid if value is not string.

Swapping key and value variables.

The keys are converted to uppercase with k.upper(), values converted to strings with str(v), and the loop uses k, v.