What are the pros and cons of Python in Machine Learning?
by Priyanka sharma Priyanka Sharma is a bloggerThe technological realm is thriving continuously at a remarkable pace. Most of the industries are executing Machine
Learning algorithms in order to optimize their commodities. With the assistance
of Machine Learning algorithms, companies are prepared to increase their
top-line expansion and enhance procedures which in turn boosts workforce
employment and consumer satisfaction.
Nowadays, Python programming language is attaining
more vogue in Machine Learning projects due to its numerous characteristics. It
is a high-level, general-purpose, and dynamic programming language that is not
recent in the market. It has been accessible for almost thirty years.
Python programming language can be found virtually
at everyplace, like web and desktop apps, machine learning, network servers,
and many more. It is primarily utilized
in small project development, but now the big firms such as Google, Facebook,
Microsoft, and Amazon Prime are also utilizing Python in implementing their
projects. It is one of the rapidly thriving programming languages, and it is
anticipated that Python will take over other languages such as JAVA in the
upcoming year.
There are considerable benefits of learning Python
and one can enroll in Python
Online Training Course to get hands-on experience.
Let’s have a
look at the windfalls of Python, which exhibits that it is the promising
programming language for Machine Learning:
- It has an outstanding collection of in-built
libraries: Python asserts an enormous number
of in-built libraries for data mining, data manipulation, and machine
learning. For example, NumPy, Scikit. Panda etc.
- Adequate
learning Curve: Python Programming
language is very convenient and manageable to understand and utilize. It
concentrates on code readability. It is a versatile and well-structured
language.
- It is a
general-purpose programming language: Well, Python is an adequate preference if the project prerequisites
are more than just data such as formulating a functional website.
- Effortless to
integrate: Python programming language
incorporates better than other languages in the business settings. It is
simple to incorporate Python with other lower-level languages such as C,
C++, or Java. Likewise, the Python-based-stack is understandable to
integrate with data scientist’s work, which enables it to bring efficiency
into production.
- Increased
productivity: Syntax in Python is
remarkably understandable and simple to discern similar to other
programming languages, whereas other programming languages remember a
different syntax. The readability syntax in Python programming language
substantiates the high productivity of development teams.
Shortcomings of
Python Programming Language: It is always
advised to utilize the correct equipment for the project enactment. We know
that a coin has two sides; likewise, Python programming language not only has
advantages but there are some downsides too.
- Insufficient speed: We know that Python is comprehended language, i.e., the code in
Python is executed line by line. Thus, Python often results in sluggish
performance as compared to other programming languages. The speed is not a
difficulty unless it is a crucial point for the project. In another way,
if high speed is not a necessity, Python services are adequate to distract
us from its speed restrictions.
- Difficulties
with threading: Python does not support
threading because of Global Interpreter Lock, i.e., GIL which is a mutex;
this authorizes only a sole thread to execute at a time.
- Not
spontaneous to the mobile environment: Python is not innate in the mobile setting, and it is understood as
a vulnerable language for mobile computing. Mobile settings such as
Android and iOS do not support Python as an accepted programming language.
- Design
limitations: We know that Python is a
dynamically-typed language which implies that it does not compel
announcing the variable type at the time of coding.
- Underdeveloped database access layers: Python’s database access coatings are not yet
expanded as compared to other widely utilized technologies such as JDBC,
i.e. Java Database Connectivity and ODBC, i.e. Open Database Connectivity.
Thus, it is not empirical to utilize it in substantial businesses.
Bottom Line:
Python is a high-level, comprehended, interactive,
and object-oriented scripting language. Python is designed to be highly
distinct. It utilizes English keywords continually whereas other languages use
punctuation, and it has periodic syntactic buildings than other languages.
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Created on Sep 30th 2020 03:46. Viewed 366 times.