Human beings are excessively leaning on machines and AI-based technology to go through their daily routines. Think about using Alexa for creating grocery lists or playing music. Think about using your car’s AI system to give commands about the GPS, music, and other updates. Think about talking to your phone to take important notes. AI and machines have become an inseparable part of our lives.
So, evidently, more and more businesses are looking up to AI and ML when it comes to application development. If you’re someone planning to create such an app and are confused about which programming language to choose, we have an answer for you. And the answer is Python. Now, why do we consider Python a suitable choice in this regard? Let’s find out:
Python: The Best Choice For AI and ML Projects
If you don’t know already, Python is a popular high-level programming language. An upgrade to languages like C, this general-purpose language is developed through the ideas of code readability, fewer code lines, and clear programs.
Why is Python Suitable for AI and ML projects?
Python is popular among developers because of the many benefits it offers, like ease of use, flexibility, abundant libraries, and a huge community of experts.
For AI and ML, this language has been a perfect choice for the following reasons:
The development process of AI and ML projects may be daunting and complex. When big companies and data scientists work on their machine learning models, they utilize their own machines to train them. These machines have powerful GPUs (Graphic Processing Units). So, the cost of training the models increases.
However, Python’s platform independence will help you reduce this hassle and cost.
With Python, when you implement your project on one machine, you can easily use it on another with zero to minimal changes. Without using an interpreter, you can distribute the Python code on all supported operating systems. These include Windows, Linus, and macOS.
The platform independence of Python is one of the biggest reasons behind its popularity. This feature of Python makes it a perfect fit for AI and ML development processes.
- Easy and Simple Codes
As we discussed, the AI and ML projects may get complex because there are heaps of data that need management. When data scientists or developers deal with such data, they may get confused if the codes are confusing.
However, with Python’s low-code barrier, this issue no longer exists. The reason is that Python’s code resembles our everyday language, English. So, the language is not alien to anybody working on the project, even if they have a minimum experience in coding.
It allows people to simply pick the language and start implementing it for the development process. The simple syntax helps people handle complex systems easily. No effort and no time is wasted in learning or understanding the language.
Yet, if you get stuck at some point and don’t understand the code, the Python community is the best place to seek help. You can ask questions or use the available documentation.
- Countless Libraries and Frameworks
Another major reason behind the popularity of Python for AI and ML development is the availability of countless compatible libraries.
Libraries are pre-written sets of code used by developers to work on different programming tasks.
The process of AI and ML development is time-consuming. It is also tricky to implement the algorithm correctly. The developers need the environment to be tested and structured perfectly before they can look for coding solutions.
To make the process simpler and reduce the development time, the developers often utilize Python libraries and frameworks.
Python is well-known for its array of libraries, including:
- Scikit-learn: Includes implementations for ML development like support vector machines, linear regression, logistic regression, etc.
- NumPy: Provides support for complex processes including data analysis and high-performance computing.
- Pandas: Suitable for tasks like general-purpose analysis of data.
- Scipy: Used for tasks like advanced data and scientific computing.
Besides these, there are many other libraries suitable for ML and AI, like spaCy, TensorFlow, Natural Language Toolkit (NLTK), Seaborn, Keras, and more.
So, the availability of so many libraries makes it easy for developers to seek help for complex tasks and reduce development time.
For ML projects, Python balances the complexity of processes with its flexibility.
You do need to recompile the source code when developing with Python. Instead, the changes can be directly implemented and you can instantly see the results. For better results and the achievement of goals, developers can combine other languages with Python without any hassle.
You can also choose between Object-Oriented Programming (OOP) and scripting. The developers can choose any programming style that they can easily implement.
Being a flexible language, Python reduces the chances of errors. The developers feel they are in complete control of their project, and they can easily work on the same.
- A Huge Community
For years, Python has been a popular programming language. So, there is no denying that people love it and share their love across a huge community.
Over the years, the Python community has grown, and there seems to be no lack of support for this open-source language. So, if you choose Python for a complex AI or ML project, the community is always there to help you through the rough patches.
You can utilize Python forums to find out the ML solutions that will help you go forward with your project. In such a huge global community, it is not uncommon to find someone dealing with the same problem as you. And fellow developers always have the right advice and guidance to resolve the issues.
So, these are the reasons why Python is one of the best programming languages for AI and ML development. Now that you have finalized the language for your project, you can hire Python developer and get the work started.
Currently, Python is being used for ML and AI projects in various domains like FinTech, healthcare, travel, and more. So, it is a winning combination. Try it out and explore the goodness of Python.
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