Why Python for Machine Learning?

Mamta Mitali

May 20, 2021
Why Python for Machine Learning?

Just about every programming language has a fanbase, and Python is no different. Python has grown as one of the most demanding programming languages among developers across the globe, from automation scripts to web development to machine learning, it’s applied everywhere. Recently, Python has been gaining new fans in special and popular segments such as data science and machine learning.

Let’s know why Python is becoming a great choice among machine learning professionals.

Machine Learning...

Machine learning is a branch of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. 

In other words, machine learning focuses on applications that learn from experience and improve their decision-making or predictive accuracy over time.

It plays a relevant role in IT, advertising, banking, transport, agriculture, logistics, healthcare, finance, cybersecurity, and numerous different industries.

Why is Python Best-Suited for Machine Learning?

Machine learning (ML)  programming languages need to be powerful, scalable, readable. Python code delivers on all three and much more. Let’s have a look at few features of Python, knowing these features will make you fall in love with Python;

Python is easy to understand

Python is usually one of the suitable programming languages because it is easy to understand, it provides a clear and readable syntax that makes it easy to understand and learn the programming fundamentals, and allows you to focus on creating solutions for your problems quickly.

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

It does not require long lines of code to get things done, allowing engineers to automate tasks with fewer lines of code.

Simple and Quick Data Validation

Machine learning’s job is to identify patterns in data. A machine learning (ML) engineer is responsible for harnessing, refining, processing, cleaning, sorting out, and deriving insights from data to create intelligent algorithms.


Python is easy while the subjects of linear algebra or calculus can be so difficult, they require the maximum amount of effort. Python can be performed rapidly which allows ML engineers to adopt an idea quickly.

Python has multiple Libraries and Frameworks

Python is already pretty popular and consequently, it has hundreds of various libraries and frameworks that can be used by developers. These libraries and frameworks are big time savers which in turn makes Python even more popular.

Many Python libraries are especially useful for Artificial Intelligence and Machine Learning. Some of them are provided here:

Keras is an open-source library that is particularly focused on experimentation with deep neural networks.

TensorFlow is a free software library that is used for many machine learning applications like neural networks.

Scikit-learn is a free software library for Machine Learning that various classification, regression, and clustering algorithms related to this. Also, Scikit-learn can be practiced in conjugation with NumPy and SciPy.

pylearn2 which is also ideal for data mining and Machine Learning, but more flexible than sci-kit-learn.

Easy syntax and human-level readability

Python is an object-oriented programming (OOPs) language that uses modern scripting and friendly syntax. Designed with almost human-level readability, the scripting environment of Python enables coders and programmers to test their hypothesis and run their algorithms very fast.

This is the reason why structural programming languages like Java, Perl, and C++ require strong coding, which is not commonly favoured for Machine Learning.

Whether you're a skilful programmer or a coding beginner, you can do a lot of stuff with Python, which is perfect for doing a complex set of Machine Learning tasks.

Visualization choices

Data is the most important aspect of Machine Learning, Artificial Intelligence, and Deep Learning algorithms. Operating with data requires heavy visualization to discover patterns and make sense of all variables and factors. To achieve that, Python software packages are the best.

Developers can produce histograms, charts, and plots for a much understanding of how data will communicate and work together. There are APIs as well that perform the visualization process easier by permitting you to outline clear reports of data.


Python is recognized as the most flexible language in machine learning. It gives various options for users. The flexibility factor decreases the possibility of errors. It allows the programmers to take the circumstances completely under control, and work on them conveniently. 

Additionally, it’s perfect for linking various data structures and works as an ideal backend. A majority of code can also be checked in the IDE, particularly for developers who’re coping with different algorithms.

Well, this list is not exhaustive, We have tried mentioning a few most important ones only.

Final Thoughts

The Python programming language has been very popular. There are several programming languages and Python is one of the best. . Many companies saw the benefits of Python for Machine Learning and why it is important for AI, and thus Python is widely used by these companies around the world.

In reality, Python is an exceptional programming language for Artificial Intelligence. It has the power to handle massive amounts of data requests concurrently. It would be fascinating to see more such integration of Python and Machine Learning in the future.

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