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International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019
851
ISSN 2229-5518
A Review on Python for Data
Science, Machine Learning and
IOT
P.N.Siva jyothi, Rohita Yamaganti
Abstract- Python is an object oriented, scripted and interpreted language for both learning and
real world programming. Python is a powerful high-level language created by Guido van Rossum.
In this paper, we will provide an introduction to the main Python software tools used for Data
science, Machine learning techniques and IOT. Briefly, this paper will first introduce Python as a
language, and give introduction about Data science, Machine learning and IOT, and then
describe packages that are popular in the Data science and Machine learning communities,
such as NumPy, SciPy, TensorFlow, Keras ,Matplotlib etc. From there, we will move to show the
importance of python for building IOT applications. We will use different code examples
throughout. To aid the learning experience, execute following examples contained in this paper
interactively using Jupiter notebooks .
Keywords: Machine learning · Data Science · IOT · Tools · Languages · Python
Introduction
1.1 Introduction to python
Python is a general-purpose,
high-level programming language
which became popular in the recent
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times .It allows programmer to write
the code in fewer lines that is not In this paper we wish to give brief
possible with other languages. The idea of python in the area of Data
important feature in Python science, IOT and Machine learning.
programming is it supports multiple Python is known to have an
programming paradigms. Python abundance of libraries that assist
provides a large set of with data analysis and scientific
comprehensive standard library computing. For example, we can
which is extensible. The main build python application which
features of Python are Simple and helps data analysts to analyze large
easy to learn, Freeware and open amounts of data for scientific
source, High level , Simple and easy computing. The prerequisites for
to learn, Freeware and open source, this paper are basic under-standing
High level programming language, of statistics, as well as some
Platform independent, Portability, experience in any C-style language.
Dynamically typed, Both procedure Some knowledge of Python is useful
oriented and Object oriented, but not a must.
Interpreted, Extensible, Embedded, An accompanying Github repository
Extensive Library. is provided to aid the tutorial. It
contains a number of notebooks of
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International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019
852
ISSN 2229-5518
python code snippets for reference. uncertainty. Python provides
It helps to go through number of various predefined modules to work
examples related to different on Data science projects.
modules of Python.
Https://github.com/mdbloice/MLDS 1.3 Introduction to Machine
Learning
The term machine learning refers to
the automated detection of
meaningful patterns in data. In the
past couple of decades it has become
a common tool in almost any task
that requires information extraction
from large data sets. We are
surrounded by a machine learning
based technology: search engines
1.2 Introduction to Data Science learn how to bring us the best
Data science is a multi- results (while placing profitable
disciplinary area that uses scientific ads), anti-spam software learns to
methods, procedures, tools and filter our email messages, and credit
systems to extract knowledge and card transactions are secured by
get insights into structured and software that learns how to detect
unstructured data. Data science is frauds. Digital cameras learn to
related to data analytics, data detect faces and intelligent personal
mining and big data. It understands assistance applications on smart-
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the phenomenon of the data. It phones learn to recognize voice
employs techniques and theories commands.
drawn from many fields within the Cars are equipped with
context of mathematics, statistics, accident prevention systems that are
computer science, and information built using machine learning
science. algorithms. Machine learning is also
widely used in scientific
applications such as bioinformatics,
medicine, and astronomy. One
common feature of all of these
applications is that, in contrast to
more traditional uses of computers,
in these cases, due to the complexity
of the patterns that need to be
detected, a human programmer
Statistics is one of the most cannot provide an explicit, fine-
important disciplines to provide detailed specification of how such
tools and methods to find structure tasks should be executed. Taking
in and to give deeper insight into example from intelligent beings,
data, and the most important many of our skills are acquired or
discipline to analyze and quantify refined through learning from our
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International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019
853
ISSN 2229-5518
experience (rather than following electromechanical systems (MEMS)
explicit instructions given to us). and the internet.
Machine learning tools are
concerned with endowing programs
with the ability to “learn “and
adapt.
As per the TIOBE index,
Python was the programming
language of the year in 2018. With a
Because machine learning is rating of 10.020%, it is also the 3rd
typically used to process large most popular language in
volumes of data, you may want to 2019.Python is mostly used for
choose a powerful low-level writing web applications, but it has
gained popularity in the IOT
language. However, if you’re only
just beginning to explore this field, it system. It is an interpreted language
might be better to start with Python. that offers readability with syntax
Python is beginner-friendly, and can without compromising the size. This
do the same thing that other coding language has a large number of
languages can, but in fewer lines of libraries; it can get more stuff done
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code.If you are interested in with fewer codes. Python’s clean
exploring machine learning with syntax is suitable for database
Python, this paper will serve as your arrangement. In case your app
guide. This is paper gives overview needs the data to be arranged in a
of programming machine learning database format or use tables.
using Python. Python is the right choice available.
Python is the right choice, for data
1.3 Introduction to IOT analysis in IOT systems. The
language is simple and can be easily
The Internet of Things deployed. Its large community helps
(IOT) is a scenario in which objects, in providing help and libraries as
animals or people are provided with and when required. It is the ideal
single identifiers and the capability language for data-intensive
to automatically transfer and the applications.
capability to automatically transfer 2. Objectives of Study
data more to a network without
requiring human-to-human or
human-To-computer 1. To conceptualize the features of
communication. IOT has evolved Python
from the meeting of wireless 2. To investigate python modules
Technologies, micro- for Data Science like Numpy
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International Journal of Scientific & Engineering Research Volume 10, Issue 12, December-2019
854
ISSN 2229-5518
which is used for matrix and development of a wide range of
vector manipulation,Scipy, the applications from simple text
2D plotting library Matplotlib etc processing to WWW browsers to
3. To focus on python modules for games.
Machine learning like Tensor
flow numerical computations for
machine learning, Keras for
neural networks and deep
learning
Each will be discussed in this
paper.
3. Related Works
3.1 Basic Features of Python
Python is a general-purpose
interpreted, interactive, object-
oriented, and high-level
programming language. It was
created by Guido van Rossum 3.2 Python for Data Science
during 1985- 1990. Like Perl,
Python source code is also These are the most essential Data
available under the GNU General Science libraries you have to
Public License (GPL). This paper know:
gives enough understanding on
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Python programming language. Numpy
Matplotlib
Python is Interpreted − Scipy
Python is processed at runtime by Numpy: Numpy will help us to
the interpreter. You do not need to manage multi-dimensional arrays
compile your program before very efficiently. Maybe it is difficult
executing it. This is similar to PERL to do that directly, but since the
and PHP. concept is a crucial part of data
Python is Interactive − you science, many other libraries (well,
can actually sit at a Python prompt almost all of them) are built on
and interact with the interpreter Numpy. Simply to say, without
directly to write your programs. Numpy it is difficult to use Pandas,
Python is Object-Oriented −
Python supports Object-Oriented
style or technique of programming
that encapsulates code within
objects.
Python is a Beginner's
Language − Python is a great
language for the beginner-level
programmers and supports the
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