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Exam AI-900 topic 1 question 53 discussion

Actual exam question from Microsoft's AI-900
Question #: 53
Topic #: 1
[All AI-900 Questions]

DRAG DROP -
You need to use Azure Machine Learning designer to build a model that will predict automobile prices.
Which type of modules should you use to complete the model? To answer, drag the appropriate modules to the correct locations. Each module may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:

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Suggested Answer:
Box 1: Select Columns in Dataset
For Columns to be cleaned, choose the columns that contain the missing values you want to change. You can choose multiple columns, but you must use the same replacement method in all selected columns.
Example:


Box 2: Split data -
Splitting data is a common task in machine learning. You will split your data into two separate datasets. One dataset will train the model and the other will test how well the model performed.

Box 3: Linear regression -
Because you want to predict price, which is a number, you can use a regression algorithm. For this example, you use a linear regression model.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-train-score

Comments

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Marskmen
Highly Voted 2 years, 11 months ago
Select Column in the dataset - 1st right Split Data - 2nd right Linear Regression - Left
upvoted 19 times
vhogstad
1 year, 8 months ago
Why not Convert to CSV on the 1st? ML models cannot work on raw data
upvoted 1 times
rdemontis
1 year, 4 months ago
Answer is correct, raw data means only that there could be null values on some rows. Once you have cleaned them you can use the dataset. If you convert data on CSV it will not solve null values issue. Instead use Column selection and clean data modules.
upvoted 6 times
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gs23mi
Highly Voted 3 years ago
see https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-deploy
upvoted 10 times
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saema
Most Recent 3 months, 1 week ago
select column split data linear regression
upvoted 1 times
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sursur
10 months, 3 weeks ago
ML models usually require data to be in a specific format. For instance, tabular data should be in rows and columns, and text data often needs to be tokenized or vectorized.
upvoted 1 times
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dimple10
1 year, 2 months ago
why not applying logistic regression then split data?
upvoted 1 times
sujitwarrier11
5 months ago
Then how would you evaluate your result? You should not evaluate your model on the same data you used to train it.
upvoted 2 times
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AdrienBnhm
1 year, 7 months ago
I think that before all, we should have a look to the dataset quality, and remove the useless features (Select column in dataset). Then, we should transform raw data in CSV (ML doesn't work on raw data, that's a fact). Finally, we split the dataset, and select a model. So we need 4 boxes, and not 3 if we want to avoid an ambiguous question... :)
upvoted 1 times
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elina_mukherjee
2 years ago
ML models cannot work on raw data . So the first one should be converted to CSV. We convert to use dataframe.
upvoted 4 times
vhogstad
1 year, 8 months ago
I agree, why is this not change ?
upvoted 1 times
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Gmtt879
2 years, 3 months ago
Solution correct
upvoted 2 times
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MohammadKhubeb
2 years, 9 months ago
Before cleaning, we must select the attribute/feature.
upvoted 4 times
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Terryfyz
2 years, 10 months ago
hey how are youguys doing
upvoted 2 times
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nuyyep23
2 years, 11 months ago
Ah..i forgot about the split data is referring to having train / test data.
upvoted 2 times
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