MICROSOFT DP-100 UPDATED DEMO, DP-100 AUTHORIZED PDF

Microsoft DP-100 Updated Demo, DP-100 Authorized Pdf

Microsoft DP-100 Updated Demo, DP-100 Authorized Pdf

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Tags: DP-100 Updated Demo, DP-100 Authorized Pdf, DP-100 Latest Exam Registration, DP-100 Sample Test Online, DP-100 Latest Exam Dumps

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Passing the DP-100 exam provides candidates with a valuable certification that demonstrates their expertise in designing and implementing data solutions on Azure. Designing and Implementing a Data Science Solution on Azure certification is recognized by employers around the world, and can help individuals to advance their careers in the field of data science and machine learning. With the increasing demand for skilled data scientists and machine learning engineers, the DP-100 Exam is an excellent way for individuals to distinguish themselves in a competitive job market.

Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q226-Q231):

NEW QUESTION # 226
You download a .csv file from a notebook in an Azure Machine Learning workspace to a data/sample.csv folder on a compute instance. The file contains 10,000 records. You must generate the summary statistics for the data in the file. The statistics must include the following for each numerical column:
* number of non-empty values
* average value
* standard deviation
* minimum and maximum values
* 25th. 50th. and 75th percentiles
You need to complete the Python code that will generate the summary statistics.
Which code segments should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 227
You are evaluating a Python NumPy array that contains six data points defined as follows:
data = [10, 20, 30, 40, 50, 60]
You must generate the following output by using the k-fold algorithm implantation in the Python Scikit-learn machine learning library:
train: [10 40 50 60], test: [20 30]
train: [20 30 40 60], test: [10 50]
train: [10 20 30 50], test: [40 60]
You need to implement a cross-validation to generate the output.
How should you complete the code segment? To answer, select the appropriate code segment in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: k-fold
Box 2: 3
K-Folds cross-validator provides train/test indices to split data in train/test sets. Split dataset into k consecutive folds (without shuffling by default).
The parameter n_splits ( int, default=3) is the number of folds. Must be at least 2.
Box 3: data
Example: Example:
>>>
>>> from sklearn.model_selection import KFold
>>> X = np.array([[1, 2], [3, 4], [1, 2], [3, 4]])
>>> y = np.array([1, 2, 3, 4])
>>> kf = KFold(n_splits=2)
>>> kf.get_n_splits(X)
2
>>> print(kf)
KFold(n_splits=2, random_state=None, shuffle=False)
>>> for train_index, test_index in kf.split(X):
print("TRAIN:", train_index, "TEST:", test_index)
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
TRAIN: [2 3] TEST: [0 1]
TRAIN: [0 1] TEST: [2 3]
References:
https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html


NEW QUESTION # 228
You need to configure the Permutation Feature Importance module for the model training requirements.
What should you do? To answer, select the appropriate options in the dialog box in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/permutation-feature-importance


NEW QUESTION # 229
You use Azure Machine Learning to train a model.
You must use a sampling method for tuning hyperparameters. The sampling method must pick samples based on how the model performed with previous samples.
You need to select a sampling method.
Which sampling method should you use?

  • A. Grid
  • B. Bayesian
  • C. Random

Answer: B

Explanation:
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-tune-
hyperparameters#sampling-the-hyperparameter-space


NEW QUESTION # 230
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create a model to forecast weather conditions based on historical data.
You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.
Solution: Run the following code:

Does the solution meet the goal?

  • A. Yes
  • B. No

Answer: B

Explanation:
train_step is missing.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-pipeline-
core/azureml.pipeline.core.pipelinedata?view=azure-ml-py


NEW QUESTION # 231
......

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