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5 Reasons why you should Use Python for AI and Machine Learning

Three interesting facts for you to ponder over:

  1. Python’s package repository offers 147,000 packages.
  2. One of the official languages most used by Google is Python.
  3. The company responsible for creating effects for the Star Wars franchise, ILM, uses Python. 

Now you want to hire Python developers. However, don’t rush. Read this article to gather the necessary knowledge first. 

In the next five minutes, this article will tell you the 5 Reasons why you should Use Python for AI and Machine Learning. Equipped with the knowledge, you would be able to take the next steps with much more conviction and know why exactly to use Python for AI and machine learning. 

By the time you finish reading this article, you’ll know why developers use Python for machine learning and AI.

Note: the information is true at the time of writing. That’s October 2022.

5 Reasons why you should Use Python for AI and Machine Learning

  1. Diverse sets of frameworks and libraries

The vast sets of offered frameworks and libraries with base-level items make Python the best programming language for machine learning

The libraries help developers to solve common programming tasks. The process helps in lowering the development time. Furthermore, the developers won’t have to reinvent the wheel or write new code from the very beginning every time.  


Check out some of the most popular Python libraries and frameworks developers use for machine learning and Artificial intelligence (AI):

  • Keras: Helps in prototyping and fast calculations. The library uses the GPU and the CPU of the computer. The library is used for deep learning.
  • Scikit-learn: The library is used for handling basic machine learning algorithms. The basic machine learning algorithms include classification, clustering, regression, and linear and logistic regressions, among others.
  • NLTK: The library is used for working with natural language recognition, processing, and computational linguistics. 
  • Pandas: The library is used for high-level analysis and data structures. The library allows developers to gather data from external sources such as MS Excel. Furthermore, the library allows developers to merge and filter data as well.
  • Matplotlib: The library is used for creating histograms, charts, and 2D plots, among other visualization forms.  
  1. Simple and consistent programming language

How does Python simplify complex predictive technologies such as Artificial Intelligence and machine learning? Here are 3 reasons:

  1. With the help of the clear code
  2. With the help of the numerous machine learning-specific libraries and frameworks
  3. With the help of the ability to shift focus from the language toward algorithms

Furthermore, if you’re asking, “Why Python is used for machine learning?” here are the reasons developers offer:

  • Python is easy to learn. Thus, developers without much knowledge of Python – and even beginners – can get the hang of the programming language without much hassle. 
  • Python comes with easily readable and concise code. Thus, the simplicity of the programming language helps developers to write reliable systems even when working with versatile workflows and complex algorithms behind Artificial Intelligence and machine learning. The process allows developers to focus on solving the machine learning issues rather than stressing over the technical nuances of the programming language.
  • Python is more intuitive than most other popular programming languages. Furthermore, the programming language is best suited for collaborative implementation. The feature is especially beneficial if multiple developers are involved in a project.
  • Python allows developers to build prototypes with ease as Python is a general-purpose language. Thus, developers can test the product for machine learning purposes in no time.
  1. Platform Independent programming language

If you’re wondering why Python language is well-performing comparatively with others when it comes to Artificial Intelligence and machine learning, platform independence is one of the answers. 

Python is compatible with all the popular operating system platforms such as:

  • macOS
  • Windows
  • Solaris
  • Linux

Thus, developers can write Python code to create standalone executable programs for all operating systems. The process allows developers to distribute and use Python on all operating systems without a Python interpreter. 

The programming language is compatible with computing services such as Amazon Web Services and Google. 

Furthermore, if you want to use your own machines with robust Graphics Processing Units (GPUs) to train the machine learning models, Python makes it possible. Furthermore, Python makes the training process cheaper and easier, thanks to the programming language’s platform-independent nature.

  1. A massive and helpful community

Let’s begin with three interesting facts for you to mull over: 

  • Python was announced as the 4th most popular programming language in the Stack Overflow 2020.
  • 8.2 million developers across the world worked with Python in 2020. The number is 7.6 million for Java.
  • Python comes with over 147,000 packages in the package repository.

Thus, you can be sure that the Python AI community is spread across the globe. You can find active Python forums where you can exchange knowledge and experience with machine-learning solutions in real-time. The forums and communities are the best places to discuss errors, help each other out, and solve problems. 

Thus, no matter what issue you’re facing right now, chances are someone has dealt with the same issue already. Therefore, you can find a solution no matter what time or date it is. 

Furthermore, you can find a bunch of resources – for both beginners and advanced developers – as Python is an open-source platform. You can find Python documentation both online and in Python forums and communities. 

The diverse set of libraries, frameworks and the free package repository helps developers to run common Python tasks without much hassle and without the need to write the code every time from the beginning. 

Furthermore, developers use Python for 27% of data science and machine learning projects combined. 

  1. A flexible programming language

Here’s what the flexibility allows:

  • No need to recompile the source code. Developers can modify the existing code and see the changes in action in no time. 
  • Developers receive an option to use scripting or OOPs. 
  • Developers can combine Python with other programming languages to reach certain goals.  

Furthermore, developers can choose between 4 programming styles to solve several issues:

  1. The functional style: Also called declarative as the style declares the required operations to be performed. The declaration comes as statements in the form of mathematical equations. 
  2. The imperative style: Comes with commands describing how a computer should perform said commands. 
  3. The procedural style: Comes with tasks in a step-by-step format. 
  4. The object-oriented style: Comes with two concepts; class and object. 

Reasons why you should Use Python for AI and Machine Learning – developers love the programming language

48.24% of developers confirmed they prefer Python as their programming language for Artificial Intelligence and machine learning.

 Furthermore, Python has been placed at the #3 position as the most popular programming language as well.

Thus, if you’re wondering why is Python used for Artificial Intelligence and machine learning, the reason is developers love to use the programming language. Thus, you’ll do well to get on the wagon and use the programming language for Artificial Intelligence and machine learning as well.   

Now that you know the 5 Reasons why you should Use Python for AI and Machine Learning, we hope the knowledge will help you make the most informed decision.


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