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November 21, 2024
The current age is the age of automation, personalization, smart devices, and digitization. If you use your phone daily, you must have seen countless ads. The cool thing about these ads is that they are curated based on your search preferences.
Other than this, the autocorrect feature of your phone, google search recommendations, etc. All these are based on two technologies, namely, AI and Machine Learning.
Both of these technologies are the future of the world. And the trend of using them is exponentially surging. As per stats,
- The valuation of the global AI market will reach up to $997.77 billion by 2028.
- Moreover, the market of Machine Learning is expected to hit the $47.29 billion mark by 2027.
The programming language that backs both of these ingenious technologies is Python. Python is one of the most preferred languages at present. It has been adopted by various companies in countless AI development solutions so far.
There are many reasons for the widespread adoption of Python, and we are going to discuss them thoroughly in this write-up. So, keep reading!
Some cool facts about Python!
- Some functions in Python can return multiple values as compared to Java and C.
- A Python file is stored as a .pyc file which acts as a dynamic engine eliminating the need for a compiler in Python.
- You can easily implement the “else” clause within the “for” loop in Python.
- Python has a variant in both C and Java.
- The Zen of Python is an immortal prayer written about Python.
Why is Python favored for AI and Machine Learning?
There is not one but many reasons for choosing Python for developing AI and Machine Learning solutions. Here are some of those reasons!
A plethora of libraries
One of the prime reasons for choosing Python for AI and Machine Learning is the libraries. Unlike other programming languages, Python has countless libraries that can be used for various applications.
A library is a module or a group of modules that have some pre-written code. This pre-written code can be used to write code further as per the developer’s need. The best thing about a library is that the developer does not have to start from scratch every time. Therefore saving a lot of time for them.
AI development solutions and Machine Learning development solutions require complex data calculations. Therefore, Python provides you with libraries like Numpy, Pandas, and others for faster computations. Here are some of the libraries of Python:
Source: Light It
- Pandas: As mentioned, Pandas is a library that is used for high-level data computation and analysis. Big data analysis is powerfully backed by Pandas. You can collect, filter, merge and even import data from excel.
- TensorFlow: Machine Learning also has a subset named deep learning. The technology is primarily used in AI applications and deals with utilizing artificial neural networks for big datasets.
- Matplotlib: To make it easy for you to visualize data in various forms like charts, histograms, 2D plots, Python provides you with Matplotlib.
- Keras: Keras has the capability to access both the CPU as well as GPU of your system. This allows it to make speedy calculations, thus making it ideal for deep learning.
- Scikit-Image: This is an innovative Python library ideal for image processing.
- Scikit Learn: Scikit learn is a Python library that is used to manage various Machine Learning algorithms such as classification, regressions, clustering, and many more.
- PyBrain: It is a library that primarily uses neural networks and reinforcement learning.
These are just some of the Python libraries. There are many others that you can use to develop powerful apps and software. However, you may also have to hire dedicated Python developers for the same.
Easy to learn
Many of you may think that Python would be tough to learn as it is used in various high-level technologies. Well, it is not! Unlike C, Java, and other code languages, Python is a cakewalk. Anyone who knows basic English can easily learn Python as it has a pretty simple syntax for doing anything.
For example, if you want to print “Hello” in Java, the syntax of the code is:
class Hello {
public static void main(String[] args) {
System.out.println(“Hello”);
}
}
The code takes up 5 lines. In contrast to this, if you want to print “Hello” in Python, the code syntax is:
Print (“Hello”)
The code is pretty simple as compared to that of Java and any other language.
As artificial intelligence and Machine Learning solutions have a lot of complexity, they require extreme focus. However, the simplicity of Python reduces the hassle of focusing on the technical details of the project. This saves a lot of time for developers and boosts productivity.
Other than being easy, Python is also consistent. The consistency of Python enables multiple developers to work on a single project simultaneously.
It runs easily on all platforms
Source: Geeky Leak
Developers may use different operating systems at their convenience. This does not mean that all of them cannot use Python. One of the key benefits of using Python for AI and Machine Learning is platform independence.
No matter if you are using Linux, Windows, Mac, or any other OS, you can easily use Python for AI development solutions and Machine Learning development. In any case, if you want to switch the OS in between your project, you are free to do it without affecting your progress on the project.
To make it simple, PyInstaller converts the file into a version fit for the other platform. You just need to tweak the lines of the code to make it work on the other platform.
Easy to Understand
As a person who knows English can learn Python easily, the simple syntax of the language can also make it easy to understand. With Python, a developer can easily code without making mistakes. Other than that, developers can also change, copy or paste the code wherever they want.
This feature of Python allows developers of the Python development company to share codes with each other without worrying about syntax.
Tools like IPython can be used for add-on functionality like testing and debugging.
Flexibility
The term flexibility is perfect for Python as it offers the developers a lot of choices for easy coding. For example, a developer can choose from Object-Oriented Programming or scripting. Moreover, Python does not need to recompile the source code again and again. The developer can apply the required changes and easily check the results instantly.
Different developers could be used to different programming styles. This does not mean that they cannot use Python. Being a flexible language, Python offers various programming styles to its developers, such as:
- OOPS: Developers are free to implement this style but only to a certain limit.
- Procedural: this style is common among beginners and is primarily used for iteration, sequencing, selection, etc.
- Functional: this is the declarative style of coding where the declaration is necessary.
- Imperative: The imperative style includes commands that detail how a computer should execute these orders. This allows you to define the order of computations, such as changing from one program state or executing another set of instructions on an already running process.
Community
Source: Fltmag
Python has great community support. Whether you are a developer or a Python enthusiast, you can easily search for answers to your questions on the internet. There are a large number of Python development companies that offer their services as well as online communities where developers share their code.
So, these are some of the top reasons to use Python for AI and Machine Learning. There are many others such as:
- Fast learning curve
- Less coding
- Versatility
- Speed
And many more!
Applications area of Python in ML and AI
There are various application areas of Python in AI and ML, such as:
- Fintech: Stripe is a Fintech startup that uses Python for AI and Machine Learning.
- Entertainment: Spotify uses Python for Machine Learning to provide recommendations to the users regarding the music.
- Social media: Instagram uses Python 3 to back its video suggestion and other features.
Final Words
As per stats, there are around 8.2 million Python developers in the world. Moreover, Python stands at number three after Javascript and HTML in terms of the maximum number of developers. These stats clearly prove that Python is highly demanding. Moreover, the above-mentioned feature raises its preference.
Python has a huge library of modules. You can freely use any of them for your project without any hassle. This saves a lot of time and effort on the part of a developer. The vast list of Python libraries allows developers to pick up the right one for their projects. All they need is a little research on the different features of each library and then compare it with their requirements before picking up the right one.
In addition, Python also gives you access to some advanced Machine Learning tools like TensorFlow, SciKit Learn, Keras, etc. There are many more such tools available that help in boosting productivity within no time. It is easy to learn and has a vast community backing it up.
If you are planning to take up a Python project, do hire dedicated Python developers as is necessary.
