Why Python is frequently used for Machine Learning?

Why Python is frequently used for Machine Learning?

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Why Python is frequently used for Machine Learning?

Currently, there is one question that is being asked by most of the Machine learning students that Why python is a better language for Machine learning programs.

The answer is very simple. Python is the most famous, and versatile language that attracts most of the programmer’s attention and becomes fun for writing codes for ML. Developers are taking more and more interest in AI and ML and their favorite language is Python which is very simple, easy, and versatile.

python machine learning
Fig. 1 Python Machine learning Algorithms

The author of IBM’s also says that Python is one of the most important languages because of its trend search results. Most of the developers mention that the Python language has less complexity and it was built for its readability. Python is so easy that anyone can understand it easily because the language is not very tough.

Below is the simple code used to find the maximum number from a list and anyone can notice that the code is written in such a nice way that it can be understood easily.

Why Python is frequently used for Machine Learning?
Figure 2: Python code to find the maximum number from the list

Have you noticed it?

It’s a pretty simple language, a Nice lookup, and simple and easy written code.

This is the biggest factor that makes Python language so different than other languages because it’s pretty easy to learn, easy to understand, and easy to write.

Python’s role in Machine Leaning is noticeable. Python not only wins the heart of other users and developers but also manage to cross other languages especially the java-script which was one of the most in-demand languages.

Why Python’s role important in Machine learning?

Now the basic question here, is why Python is so vital In Machine Learning and AI algorithms?


Machine learning is actually just a term or we can say it’s a simple term used for using the data sets or training the data sets to make the machine able to make intelligent and vital decisions.

According to Machineelearning.com, Machine learning is just nothing but it plays important role in identifying patterns in the data.

For Machine learning engineers, one of the basic steps is actually finding the data, processing, extracting, cleaning, and arranging it. After this, he can easily understand the data and can process to make intelligent algorithms. Machine learning data trainers love to train a high amount of data for creating algorithms for ECG scanning, Neurosciences, and even for every field.

If we ask the data scientists, Python developers, or engineers that why people are recommending Python, most of them answered that it is because it is easy to learn and easily understandable.

Even in difficult concepts of engineering, Mathematics, etc sometimes the functions are hard to calculate and it requires a high amount of time, but ML engineers can implement in no time with the help of Python and this is the reason that ML engineers are also charging high salaries.

Role of Libraries and Packages:

There is another reason that why Python is far better is because of their Packages, and libraries.


Packages and Libraries play an important role, actually very much important. There are so many libraries present in the Python through which ML engineers can finish their work even faster.

  • For example, there are Scikit-learn library which is being used for handling regression, mathematics, basic ML problems, and even classification
  • Another library is Matplotlib which plays an important role in drawing graphs, histograms, and charts.
  • Another library is Pandaswhich is also important because it helps in analyzing high-level data structures and can also be used for merging, gathering, and filtering of data.
  • One library named Scikit-image plays important role in image processing. Through this, the ML engineers can easily process the images.
  • There is another library which is called PyBrain and this library is being used for neural networks.

There are many other libraries that can be found PyPI repository.

So basically, the importance of Python can be judged from these libraries and packages which plays an important role to make Python better than other languages. This is the reason that Machine learning and AI engineers are using Python as a frequent language for programing intelligent data algorithms. 

Value of Data and data sets:

How you forget the data?
Off course,

Data is the key here. Data is a thing on which everyone completely depends on. For example, if someone wants to create a program on the ECG machine, they must find the data set for the heartbeat classifications data which can be present in processed on the unprocessed form.

Now if, the data is big, unstructured, or bad. Python libraries will help to clean the data set. So, if we want to solve the machine learning problem, we have to stick with Pandas and scikit.

Another question, comes around, how we can understand Python?

I know, above we say that Python is very easy, it’s easy to understand and Bla… blaa… blaaa.a….
No new comments can say how it is an easy man? I really can not understand it and you are saying easy?
Oh I see,…
I have figured a way which is…
Python can be learned easily by following these below steps.

  1. Learn python in hard ways:It is important to learn python in hard ways. I start don’t take it very simple. There can be indentation problems which are pretty hard to tackle at the start. So just watch some good tutorials to understand the python basic codes before jumping into a broader picture.


  1. It is necessary to understand the basic steps of Python or even data structures:

    It’s not that easy to become a Machine learning engineer or data scientist. First of all, it is necessary to understand the basic steps of Python and data structures. First, understand simple and basic things before going towards the implementation steps.
why python for machine learning
Fig. 3: why python for machine learning
  1. Role of implementation in Machine learning:If you keep trying to implement difficult algorithms in Machine learning, it will make it too easy for you to learn and reading algorithms. So implementation and applying concepts are the key here.


  1. Keep the things simple

Whenever you want to learn or creating code, you just need to keep in mind that there can be another same processed code or can be well-explained functionality. So it is important to always seek guidance.

Concluding remarks:

Well, its time to close the chapter. It has been a clear lesson that why python is so simple and easy and why it becomes a preferred and recommended language.

The simple answer is because of its conciseness, readability, versatility, and because of some easy algorithms and functions. The more and more interest in machine learning experts in Python is making Python more valuable than other languages.

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