The document provides an overview of using Python for machine learning, detailing libraries such as NumPy and frameworks that simplify model development. It covers installation steps for Anaconda, significant features of Python, and includes practical examples and exercises related to NumPy operations. Additionally, it includes references for further reading and video resources for learning.

1. PYTHON FOR MACHINE
LEARNING
Dr. Amanpreet Kaur​
Associate Professor,
Chitkara University,
Punjab

2. CONTENTS TO BE STUDIED
• Introduction to Python Programming
• Python for Machine Learning
• Python Libraries used in Machine Learning
• NumPy
• NumPy Questions
• References

3. PYTHON FOR MACHINE
LEARNING (ML)
• A Python framework is an interface or tool that allows developers to
build ML models easily.
• without getting into the depth of the underlying algorithms.
• Python libraries are specific files containing pre-written code that can be
imported into your code base by using Python’s import feature.
• This increases your code reusability.
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4. PYTHON FOR MACHINE
LEARNING (ML)
• A Python framework can be a collection of libraries intended to build a
model (e.g., machine learning) easily,
• without having to know the details of the underlying algorithms.
• An ML developer, however, must at least know how the algorithms work in
order to know what results to expect, as well as how to validate them.
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5. FEATURES OF PYTHON
PROGRAMMING
• Used in Various Domains ( Artificial Intelligence, Machine Learning, Deep
Learning )
• Python is Object Oriented
• Python is Open source
• Shift from one system to another
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6. INSTALLATION OF ANACONDA
• Visit Anaconda.com/downloads
• Select Windows
• Download the .exe installer
• Open and run the .exe installer
• Open the Anaconda Prompt and run some Python code
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Figure- 1 Anaconda Distribution [1]

7. PYTHON LIBRARIES USED IN
MACHINE LEARNING
• NumPy
• SciPy
• Scikit – Learn
• Pandas
• Matplotlib
• TensorFlow
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8. NUMPY
• NumPy is a well known general-purpose array-processing package.
• An extensive collection of high complexity mathematical functions make
NumPy powerful to process large multi-dimensional arrays and matrices.
• NumPy is very useful for handling linear algebra, Fourier transforms, and
random numbers.
• Define arbitrary data types and easily integrate with most databases.
• NumPy can also serve as an efficient multi-dimensional container for any
generic data that is in any datatype.
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9. OPERATIONS USING NUMPY
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Using NumPy, a developer can perform the following operations −
Mathematical and logical operations on arrays.
Fourier transforms and routines for shape manipulation.
Developer can perform Operations related to linear algebra.
NumPy has in-built functions for linear algebra and random number generation.
Installation of NumPy
pip install numpy

10. 10
• Object defined in NumPy is an N-dimensional array type called ndarray.
• It describes the collection of items of the same type.
• Items in the collection can be accessed using a zero-based index.
• Every item in an ndarray takes the same size of block in the memory.
• Each element in ndarray is an object of data-type object (called dtype).
• Any item extracted from ndarray object (by slicing) is represented by a Python object of one of
array scalar types.
Figure-1.2 Relationship between ndarray, data type object (dtype) and array scalar type [6]

11. PROGRAM TO PRINT FIRST 25
PRIME NUMBER
11
• def isPrime(num):
for i in range(2,num):
if (num % i) == 0:
return False
else:
return True
print("prime numbers")
count, num=0, 2
while count<25:
if isPrime(num):
print(num)
count+=1
num+=1
• Output-Prime Numbers
• 2
• 3
• 5
• 7
• 11
• 13
• 17
• 19
• 23
• 29
• 31
• 37
• 41
• 47
• 53
• 59

12. NUMPY(ONE DIMENSIONAL) 12
# this is one dimensional array
import numpy as np
a = np.arange(24)
#Function return the number of
dimensions of an array.
a.ndim
# now reshape it
b = a.reshape(2,4,3)
b #print b
# b is having three dimensions
Result-
$python main.py
[[[ 0 1 2]
[ 3 4 5]
[ 6 7 8]
[ 9 10 11]]
[[12 13 14]
[15 16 17]
[18 19 20]
[21 22 23]]]

13. NUMPY-QUESTIONS
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• Write a Python program to print Factorial of given numbers.
• Write a Python program to print all Prime numbers in an Interval.
• Write a python program to sort the elements of an Array in Ascending order.
• Write a python program to print the Fibonacci series.
• Write a Python program to copy all elements of one array into another array.
• Write a Python program to print the elements of an array present on even position

14. PYTHON PROGRAMMING-
ANACONDA
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• Anaconda is a free and open source distribution of the Python and R programming
languages for large-scale data processing, predictive analytics, and scientific
computing.
• The advantage of Anaconda is that you have access to over 720 packages that can
easily be installed with Anaconda's Conda, a package, dependency, and
environment manager.
• Anaconda distribution is available for installation
at https://www.anaconda.com/download/. For installation on Windows, 32 and 64
bit binaries are available −

15. PYTHON PROGRAMMING
15
Online Compiler:-
https://dataplatform.cloud.ibm.com/
https://jupyter.org/

16. PYTHON PROGRAMMING
16
E Books-
• Peter Harrington “Machine Learning In Action”, DreamTech
Press
• Ethem Alpaydın, “Introduction to Machine Learning”, MIT Press
Video Links-
• https://www.youtube.com/watch?v=BRMS3T11Cdw&list=PL3pGy4HtqwD2a
57wl7Cl7tmfxfk7JWJ9Y
• https://www.youtube.com/watch?v=EWmCkVfPnJ8&list=PL3pGy4HtqwD2a
57wl7Cl7tmfxfk7JWJ9Y&index=3

17. THANK YOU
aman_preet_k@yahoo.co.in