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NEW QUESTION: 1

A. Option B
B. Option C
C. Option A
D. Option D
Answer: A,D

NEW QUESTION: 2
You are creating a machine learning model in Python. The provided dataset contains several numerical columns and one text column. The text column represents a product's category. The product category will always be one of the following:
* Bikes
* Cars
* Vans
* Boats
You are building a regression model using the scikit-learn Python package.
You need to transform the text data to be compatible with the scikit-learn Python package.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: pandas as df
Pandas takes data (like a CSV or TSV file, or a SQL database) and creates a Python object with rows and columns called data frame that looks very similar to table in a statistical software (think Excel or SPSS for example.
Box 2: transpose[ProductCategoryMapping]
Reshape the data from the pandas Series to columns.
Reference:
https://datascienceplus.com/linear-regression-in-python/

NEW QUESTION: 3
Using customer-supplied information, you have designed a solution using a Dell EMC Unity 400F with 250
drives. The customer now wants to increase the drive count to 340 drives at the lowest cost.
Which Unity model configuration should be recommended?
A. Upgrade to a Unity 500F and add two 25-drive DAEs
B. Keep the Unity 400F and add four 25-drive DAEs
C. Keep the Unity 400F and add two 80-drive DAEs
D. Upgrade to a Unity 500F and add two 80-drive DAEs
Answer: C

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