MATLAB Vs Python: Difference Between Matlab & Python [2024]

One of the trending debates in the scientific and computing community is that is MATLAB vs. Python. Often, people in the scientific community talk about transitioning from MATLAB to Python.

Top Machine Learning and AI Courses Online

Master of Science in Machine Learning & AI from LJMU		Executive Post Graduate Programme in Machine Learning & AI from IIITB
Advanced Certificate Programme in Machine Learning & NLP from IIITB	Advanced Certificate Programme in Machine Learning & Deep Learning from IIITB	Executive Post Graduate Program in Data Science & Machine Learning from University of Maryland
To Explore all our certification courses on AI & ML, kindly visit our page below.
Machine Learning Certification

While MATLAB is a robust computing environment for mathematical or technical computing operations involving arrays, matrices, and linear algebra, Python is also gaining popularity in the computing area. This is because Python incorporates MATLAB’s computational power and facilitates speedy and easy development of scientific applications. Check out our data science courses to learn more about MATLAB and Python.

Trending Machine Learning Skills

AI Courses	Tableau Certification
Natural Language Processing	Deep Learning AI

Enrol for the Machine Learning Course from the World’s top Universities. Earn Masters, Executive PGP, or Advanced Certificate Programs to fast-track your career.

In this article, we’ll explore the differences between MATLAB and Python.

MATLAB vs. Python: What are they?

MATLAB

MATLAB is both a commercial numerical computing environment and programming language. In fact, it is one of the most advanced and well-designed programming language for computing. In the late 1970s, Cleve Moler began the development of MATLAB. It is a multi-paradigm computing environment and language developed by MathWorks.

It is an excellent tool for matrix manipulations, data plotting, implementing algorithms, and developing user interfaces. Even though MATLAB is designed primarily for numerical computation functions, it allows for symbolic computation using the MuPAD symbolic engine.

Python

Python is an open-source, high-level, general-purpose programming language. It was developed by Guido van Rossum and released in 1991. Simplicity lies at the core of Python, and hence, it uses the OOP approach to help developers write precise and logical code for small and large projects.

Python supports multiple programming paradigms, such as procedural programming, OOP, and functional programming. Apart from its neat syntax and code readability features, Python’s best aspect is that it comes equipped with a host of standard libraries for accomplishing different programming and computing tasks.

MATLAB vs. Python: The key differences

Let’s look at some of the main differences between MATLAB and Python:

Nature

MATLAB is closed-source software and a proprietary commercial product. Thus, you need to purchase it to be able to use it. For every additional MATLAB toolbox you wish to install and run, you need to incur extra charges. The cost aspect aside, it is essential to note that since MATLAB is specially designed for MathWorks, its user base is quite limited. Also, if MathWorks were to ever go out of business, MATLAB would lose its industrial importance.

Unlike MATLAB, Python is an open-source programming language, meaning it is entirely free. You can download and install Python and make alterations to the source code to best suit your needs. Due to this reason, Python enjoys a bigger fan following and user base. Naturally, the Python community is pretty extensive, with hundreds and thousands of developers contributing actively to enrich the language continually. As we stated earlier, Python offers numerous free packages, making it an appealing choice for developers worldwide.

Syntax

The most notable technical difference between MATLAB and Python lies in their syntax. While MATLAB treats everything as an array, Python treats everything as a general object. For instance, in MATLAB, strings can either be arrays of strings or arrays of characters, but in Python, strings are denoted by a unique object called “str.” Another example highlighting the difference between MATLAB and Python’s syntax is that in MATLAB, a comment is anything that starts after the percent sign (%). In contrast, comments in Python typically follow the hash symbol (#).

IDE

MATLAB boasts of having an integrating development environment. It is a neat interface with a console located in the center where you can type commands, while a variable explorer lies on the right, you’ll find a directory listing on the left.

On the other hand, Python does not include a default development environment. Users need to choose an IDE that fits their requirement specifications. Anaconda, a popular Python package, encompasses two different IDEs – Spyder and JupyterLab – that function as efficiently as the MATLAB IDE.

Check out all trending Python tutorial concepts in 2024

Tools

Programming languages are usually accompanied by a suite of specialized tools to support a wide range of user requirements, from modeling scientific data to building ML models. Integrated tools make the development process easier, quicker, and more seamless.

Although MATLAB does not have a host of libraries, its standard library includes integrated toolkits to cover complex scientific and computational challenges. The best thing about MATLAB toolkits is that experts develop them, rigorously tested, and well-documented for scientific and engineering operations. The toolkits are designed to collaborate efficiently and also integrate seamlessly with parallel computing environments and GPUs. Moreover, since they are updated together, you get fully-compatible versions of the tools.

Read: 15 Interesting MATLAB Project Ideas & Topics For Beginners

As for Python, all of its libraries contain many useful modules for different programming needs and frameworks. Some of the best Python libraries include NumPy, SciPy, PyTorch, OpenCV Python, Keras, TensorFlow, Matplotlib, Theano, Requests, and NLTK. Being an open-source programming language, Python offers the flexibility and freedom to developers to design Python-based software tools (like GUI toolkits) for extending the capabilities of the language.

Popular AI and ML Blogs & Free Courses

IoT: History, Present & Future	Machine Learning Tutorial: Learn ML	What is Algorithm? Simple & Easy
Robotics Engineer Salary in India : All Roles	A Day in the Life of a Machine Learning Engineer: What do they do?	What is IoT (Internet of Things)
Permutation vs Combination: Difference between Permutation and Combination	Top 7 Trends in Artificial Intelligence & Machine Learning	Machine Learning with R: Everything You Need to Know
AI & ML Free Courses
Introduction to NLP	Fundamentals of Deep Learning of Neural Networks	Linear Regression: Step by Step Guide
Artificial Intelligence in the Real World	Introduction to Tableau	Case Study using Python, SQL and Tableau

Conclusion

Despite having an active community and excellent standard packages, Python fails to match up to MATLAB in one particular area – the Simulink Toolbox. This toolbox extends MATLAB’s capabilities for signal processing and modeling in a graphical interface. Python lacks a graphical interface that can perform these advanced functions.

Overall, both MATLAB and Python are excellent tools. While one is designed for specific tasks (MATLAB), another can perform a wide variety of generic operations.

If you’re interested to learn more about MATLAB, machine learning, and its relevant topics, check out IIIT-B & upGrad’s PG Diploma in Machine Learning & AI which is designed for working professionals and offers 450+ hours of rigorous training, 30+ case studies & assignments, IIIT-B Alumni status, 5+ practical hands-on capstone projects & job assistance with top firms.

If you are curious to learn about data science, check out IIIT-B & upGrad’s Executive PG Programme in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.

Frequently Asked Questions (FAQs)

1. What are the major differences between MATLAB and Python?

Python is a high-level language, it is more user friendly, more readable and more portable. MATLAB is a low-level language and not good at some algorithms such as bioinformatics. MATLAB has the function of the matrix, and Python can use NumPy, and the library can achieve similar results. MATLAB has very strong mathematical calculation ability, Python is difficult to do. Python has no matrix support, but the NumPy library can be achieved. MATLAB is particularly good at signal processing, image processing, in which Python is not strong, and performance is also much worse.

2. Is MATLAB better than Python for machine learning?

It depends on your goals and resources. If you want to focus on machine learning, Python has its own libraries as well (e.g. Scikit-learn), which are very powerful, and there are also some libraries built by the community (e.g. PyBrain). MATLAB is focused more on numerical computing, so if you're mostly interested in theoretical aspects of machine learning, then MATLAB could be the better choice. It's also worth mentioning that the most popular machine learning frameworks (e.g. Scikit-learn) are written in Python.

3. Which is faster, MATLAB or Python?

According to this benchmark, MATLAB is faster than Python. But this benchmark is not done on a real time algorithm. So, we guess it is difficult to use numbers as a definitive answer. There are two very different ways to measure speed in this world. First, there is the speed at which an algorithm solves a problem. The second type is the speed at which a program runs. The former is better measured with something like Numerical Recipes or similar. The latter is better measured with some production code.

Suggested Blogs

5438

Artificial Intelligence course fees

Artificial intelligence (AI) was one of the most used words in 2023, which emphasizes how important and widespread this technology has become. If you

by venkatesh Rajanala

29 Feb 2024

6176

Artificial Intelligence in Banking 2024: Examples & Challenges

Introduction Millennials and their changing preferences have led to a wide-scale disruption of daily processes in many industries and a simultaneous g

by Pavan Vadapalli

27 Feb 2024

75637

Top 9 Python Libraries for Machine Learning in 2024

Machine learning is the most algorithm-intense field in computer science. Gone are those days when people had to code all algorithms for machine learn

by upGrad

19 Feb 2024

64469

Top 15 IoT Interview Questions & Answers 2024 – For Beginners & Experienced

These days, the minute you indulge in any technology-oriented discussion, interview questions on cloud computing come up in some form or the other. Th

by Kechit Goyal

19 Feb 2024

152992

Data Preprocessing in Machine Learning: 7 Easy Steps To Follow

Summary: In this article, you will learn about data preprocessing in Machine Learning: 7 easy steps to follow. Acquire the dataset Import all the cr

by Kechit Goyal

18 Feb 2024

908757

Artificial Intelligence Salary in India [For Beginners & Experienced] in 2024

Artificial Intelligence (AI) has been one of the hottest buzzwords in the tech sphere for quite some time now. As Data Science is advancing, both AI a

by upGrad

18 Feb 2024