Machine Learning is one of the most dynamic fields, and it is a subset of AI (Artificial Intelligence ). Based on this, Machine Learning machines can make predictions based on experience or data.
Various programming languages can be used for machine learning, but Python is the most prevalent language used in machine language. And here in this article, I will mention some of the essential reasons why python is so popular in machine learning. So please read this complete article for more details.
If I speak about why Python is so prevalent in machine learning? In short, then I should say that it is a very popular language and very easy to use. And besides that, the readability of this programming language is very good, and there are numerous libraries and functions attached to Python that you can use for any kind of coding errors or coding problems. These are some common reasons that most Developers for companies use Python for machine learning.
Besides these factors, there are other constituents also available, and in the below section, I have mentioned all those factors one by one. So please stick with us.
5 Reasons Why Python is so Popular in Machine Learning?
Easy to Use :
The first essential reason why Python is so popular in machine learning is that it is very comfortable to use in comparison with other programming languages.
It generally means that the syntax of the Python programming language is very simple and very easy.
If you have some knowledge of any kind of Computer programming, then you can undoubtedly understand all the concepts of python.
And you can discover this programming language very quickly and within a very short period of one month to 3 months.
Because of its simplicity, most developers and corporate companies ratify this programming language for their research works and their development work.
Short Code :
This is another good advantage of using the Python programming language.
With the help of this programming language, you will be able to implement your code within short lines, In comparison with other programming languages.
If I provide an example, then within Java programming language, if you write 200 words or 300 words lines of code, then the same work you can do within Python programming within 60 or 70 words lines of code.
Libraries and Frameworks:
Python has hundreds of libraries that contain numerous frameworks as an open-source programming language.
And all these frameworks are beneficial for the developers to complete their work.
NumPy and Pandas are some of the libraries that a Python developer uses.
- NumPy: It is generally used to create multi-dimensional arrays besides that if you want to perform various operations with arrays, then you can use this NumPy library.
- Pandas: This library helps you read data from different sources. You can efficiently retrieve the data. And then, with the help of data series, you can do lots of operations.
- Seaborn: This library includes some of the most statistical analyses So you can visualize the data set Along with that you can also perform statistical analysis On that specific data.
- Scikits Learn: In this library, most machine learning algorithms are present. So if you want to implement any kind of machine learning algorithm, Then you can call that and use it within your problem statement.
Multiple Functionalities :
Besides these things, Python has multiple functionalities, which you can use in several areas.
It is used to create web-based applications, Web Services, Web scraping, and several other things.
So these functionalities make Python much more familiar to use in machine learning and other areas also.
Community support :
Many developers are using Python skills to increase their machine-learning knowledge.
Apart from that, they are also using python for implementing various deep-learning projects.
If you go into Google and search about this, then you will get various resources such as GitHub links, YouTube videos, blogs, and website articles Where machine learning is explained from the basics.
And this all happens because of the Python programming language.
Many top companies like Google, Facebook, and Amazon use python to implement Most of their products.
Is Python Necessary for Machine Learning?
Well, there are several programming languages that you can use for Machine Learning.
Some programming languages like – Java, Scala, and some others.
But in comparison with Python, these languages are not so compatible with Machine Learning.
Numerous libraries are present within Python Programming, and these are helpful for Machine Learning.
And these libraries and features do not exist within other programming languages.
Therefore, learning Python programming for Machine Learning is not mandatory, but it is the most preferred programming language used for machine learning.
Scope of Python in Machine Learning
There are various scopes available for Python in Machine Learning. Because it is the most demandable programming language used for Machine Learning.
And this programming language is not only used for Machine Learning and besides that but is also used for Artificial Intelligence.
Python is also used in several other areas, so this programming language’s scopes are much higher than the other programming language.
Advantages of Python in Machine Learning
- Availability of various frameworks.
- It is very useful.
- It has very good community support.
- The readability of this code is very good and very clear.
Final Thought:
In this article, I have mentioned some of the essential causes and advantages of using Python programming within Machine Learning.
But besides that, here, I also want to state that it is not the only programming language for Machine learning besides that, there are several other programming languages available such as – java, and Scala, which are also useful for Machine Learning. But Python is the most popular one in this field.
I hope you have liked this article, and if you have any kind of inquiry, then you can ask me in the comment section.
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