# (Python Example for Beginners)

Write a NumPy program to create a 5×5 array with random values and find the minimum and maximum values.

Sample Solution :

Python Code :

``````
import numpy as np

x = np.random.random((5,5))
print("Original Array:")
print(x)

xmin, xmax = x.min(), x.max()
print("Minimum and Maximum Values:")
print(xmin, xmax)
``````

Sample Output:

```Original Array:
[[ 0.3839264   0.6527485   0.41092465  0.63987331  0.72739435]
[ 0.1711146   0.7542493   0.30799339  0.79689356  0.92014308]
[ 0.14420449  0.28689129  0.69339598  0.26608753  0.20895817]
[ 0.20215693  0.36993965  0.21283682  0.33183608  0.92672618]
[ 0.25734144  0.01083637  0.41502065  0.90604563  0.92236538]]
Minimum and Maximum Values:
0.0108363710034 0.926726177113```

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## Two Machine Learning Fields

There are two sides to machine learning:

• Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
• Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
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