In the NumPy function, the data preparation technique that is used to help machine learning algorithms is called the reshape technique or function
For better understanding, let us explain what the reshape function means
- The numpy package helps to give the right tools for scientific and mathematical computations in python
. it includes functions that cam be used to perform common linear algebra operations, fast Fourier transforms, and statistics
The reshape function simply alter or change the row and column arrangement of data in numpy function and it is said to just give new shape to an array without the altering of its data.
from the above, we can therefore say that the answer In the NumPy function, the data preparation technique that is used to help machine learning algorithms is called the reshape technique or function is correct
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Answer:
In HTML file
<body style="background-color:orange;">
Or
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body {
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}
Answer:
- import math
-
- def standard_deviation(aList):
- sum = 0
- for x in aList:
- sum += x
-
- mean = sum / float(len(aList))
-
- sumDe = 0
-
- for x in aList:
- sumDe += (x - mean) * (x - mean)
-
- variance = sumDe / float(len(aList))
- SD = math.sqrt(variance)
-
- return SD
-
- print(standard_deviation([3,6, 7, 9, 12, 17]))
Explanation:
The solution code is written in Python 3.
Firstly, we need to import math module (Line 1).
Next, create a function standard_deviation that takes one input parameter, which is a list (Line 3). In the function, calculate the mean for the value in the input list (Line 4-8). Next, use the mean to calculate the variance (Line 10-15). Next, use sqrt method from math module to get the square root of variance and this will result in standard deviation (Line 16). At last, return the standard deviation (Line 18).
We can test the function using a sample list (Line 20) and we shall get 4.509249752822894
If we pass an empty list, a ZeroDivisionError exception will be raised.
Answer: B
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