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Why Python is the Best Language for Machine Learning and AI ?

Here are the 5 summaries from different articles, answering same question “How Python is Useful in Machine Learning and AI ? ” and link to full article is also provided for respective summaries. 

Don’t forget to ask your programming related doubt in comments below.

CONCLUSION at the end ! 

SUMMARY 1: Why Should Python be used in Machine Learning  ?(analyticsinsight.net)

An ML engineer is answerable for harnessing, refining, processing, cleaning, sorting out, and deriving insights from data to create clever algorithms.

Python can be executed rapidly which allows ML engineers to approve an idea immediately.

Python’s libraries and frameworks are truly valuable in saving time which makes Python significantly more well-known.

Developers should think not about how to write, but rather what to write, all things considered.

Python developers are excited about making code that is not difficult to read. That more data scientists can become experts rapidly and thus, they can engage in ML projects.

SUMMARY 2: Python for AI and Machine Learning (steelkiwi.com)

While complex algorithms and versatile workflows stand behind machine learning and AI, Python’s simplicity allows developers to write reliable systems.

Others point out the many frameworks, libraries, and extensions that simplify the implementation of different functionalities.

It’s generally accepted that Python is suitable for collaborative implementation when multiple developers are involved.

Python, with its rich technology stack, has an extensive set of libraries for artificial intelligence and machine learning. Python is supported many platforms including Linux, Windows, and macOS.

In the Python Developers Survey 2020,

we observe that Python is commonly used for web development. At first glance, web development prevails, accounting for over 26% of the use cases shown in the image below. However, if you combine data science and machine learning, they make up a stunning 27%. SOURCE: JETBRAINS.COM

Online repositories contain over 140,000 custom-built Python software packages. These packages cater to machine learning and help developers detect patterns in big sets of data.

For any task you may have, the chance is pretty high that someone else out there has dealt with the same problem. You won’t be alone and are sure to find the best solution to your specific needs if you turn to the Python community.

R has packages such as Gmodels, Class, Tm, and RODBC that are commonly used for building machine learning projects. Compared to Python, R has a reputation for being slow and lagging when it comes to large-scale data products.

SUMMARY 3: Why is the Python the best suited programming language for Machine Learning ? (geekforgeeks.com)

It is simple with an easily readable syntax and that makes it well-loved both seasoned developers and experimental students.

The simplicity of Python means that developers can focus on actually solving the Machine Learning problem rather than spend all their time (and energy!)

It allows developers to complete more work using fewer lines of code. Python has multiple Libraries and Frameworks

Python is already quite popular and consequently, it has hundreds of different libraries and frameworks that can be used developers.

Also, Scikit-learn can be used in conjugation with NumPy and SciPy.

Python has been around since 1990 and that is ample time to create a supportive community. Because of this support, Python learners can easily improve their Machine Learning knowledge, which only leads to increasing popularity.

In fact, Google is single-handedly responsible for creating many of the Python libraries for Machine Learning such as Keras, TensorFlow, etc.

Python is Portable and Extensible

This is an important reason why Python is so popular in Machine Learning.

 There are many data scientists who prefer using Graphics Processing Units (GPUs) for training their ML models on their own machines and the portable nature of Python is well suited for this. To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

SUMMARY 4 :  Reasons why Python is good for AI and Machine Learning ? (towardsdatascience.com)

A great choice of libraries is one of the main reasons Python is the most popular programming language used for AI.

It allows merging and filtering of data, as well as gathering it from other external sources like Excel, for instance.

It allows fast calculations and prototyping, as it uses the GPU in addition to the CPU of the computer.

Matplotlib for creating 2D plots, histograms, charts, and other forms of visualization. Programmers can combine Python and other languages to reach their goals.

The flexibility factor decreases the possibility of errors, as programmers have a chance to take the situation under control and work in a comfortable environment. Again, this saves time and money for tests on various platforms and makes the overall process more simple and convenient.

When it comes to cryptocurrency, Python is used to build solutions like Anaconda to effectively analyze the market, make predictions and visualize data.

Growing popularity leads to the growing demand for Python programmers inside the data science community, and it’s a wise choice to choose a language that’s in high demand, as, in the future, it will allow even more functionality.

SUMMARY 5 :  Why Python for Machine Learning ? (pythonbasics.org)

To reiterate, Machine Learning is simply recognizing patterns in your data to be able to make improvements and intelligent decisions on its own. Python is the most suitable programming language for this because it is easy to understand and you can read it for yourself.

Its readability, non-complexity, and ability for fast prototyping make it a popular language among developers and programmers around the world.

Many of these inbuilt libraries are for Machine Learning and Artificial Intelligence, and can easily be applied out of the box. sklearn, scikit-learn, a machine learning module for python helps to do so.

Even if you only have basic knowledge of the Python language, you can already use if for Machine Learning because of the huge amount of libraries, resources, and tools available for you.


The main reason is the presence of huge libraries and packages like scikit learn, tensorflow, numpy, pandas, matplotlib…etc. which have already done the implementation part. You just have to basic understanding of algorithm and you can fine tune any algorithm according to your use case.

A lot of resource and huge community support, easy syntax and many things together makes python the best fit for Machine Learning and AI. 

R, Julia, Scalia are also some of the languages used for Machine Learning and AI but don’t have such community support as compared to python.

You can read any article in depth.

Hope now your doubt would have cleared. If not yet, or have any other doubt you can comment down below. And You can also help others answering their doubts. You can read more about us in About Us


If I left something or you feel that something could be more well addressed, please leave a comment.

Chitranshu Harbola

Self taught programmer, Web Developer and an aspiring Machine learning engineer cum Data Science student

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