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programming

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Programming refers to a technological process for telling a computer which tasks to perform in order to solve problems. You can think of programming as a collaboration between humans and computers, in which humans create instructions for a computer to follow (code) in a language computers can understand.While the names of the coding paradigms sometimes vary, most experts agree on four primary types of code: imperative, functional, logical, and object-oriented. Alternative names and other primary types may include procedural, scripting, and database programming.

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# -*- coding: utf-8 -*-
# """assignment[1].ipynb
# """
import numpy as np

"""# Task 1:"""

# Q : 1
a = 3 *np.sqrt(16) + np.abs(-5)
a

# Q : 2
b = 2 **3 - np.log10(100)+ np.abs(-2)
b

# Q : 3
c = np.sqrt(25)+0.5* 4**2
c

# Q : 4
d = np.abs(-3 * np.log2(8)) + np.sqrt(144)
d

e = np.exp(2)+ np.log(10)-1/np.abs(-1)
e

np.sqrt(81)+np.log2(32) -3**2

4 * np.sqrt(36) -np.log(1)+ np.abs(-4)

np.sqrt(49) +1 /2* np.exp(2) -np.abs(np.log10(100))

3**3 +np.log2(16) - np.abs(-np.sqrt(64))

"""Task 2:"""

A = np.array([2,4,6])
result = np.square(A) + np.sqrt(A) - np.abs(A)
result

B = np.array([1 , 3 , 5])
value = np.exp(B) - np.log10(B) + np.abs(B)
value

C = np.array([0.1 , 0.5 ,1.0])
Evaluate = np.sqrt(C) + 1 / (C**2) - np.log(C)
Evaluate

D = np.array([-2 , 0 , 2])
NumPy = np.abs(D) + np.sqrt(D) - np.log2(D)
NumPy

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Uploaded on
February 26, 2024
File latest updated on
February 26, 2024
Number of pages
5
Written in
2023/2024
Type
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Professor(s)
Aliza javed
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