With the rapid increase in the complexity and volume of the data, it has become necessary to use highly advanced processing and analyzing technologies such as artificial intelligence and machine learning. By processing a large amount of data (surprisingly, in a few minutes) to bring out useful information, AI and ML are helping businesses to improve efficiency, predict future, minimize cost and efforts, and boost productivity.
Considering the huge benefits of these two technologies, it would be no wonder to see industries worldwide adopting AI and ML in their processes. This growing demand for integrating artificial intelligence and machine learning in the business processes is also increasing the demand for AI and ML experts as well as AI development and machine learning development companies.
When it comes to developing an AI and ML-based application, Python is considered as the best programming language for writing codes. Wondering why? Here are the top five reasons to choose Python for machine learning and artificial intelligence development:
- Flexibility and Readability
Being a flexible programming language, Python provides developers the freedom to select from scripting or object-oriented programming. Also, it relieves them from recompiling the source code for any modification. The language can also be used together with any other language to achieve desired outcomes.
Python’s flexibility permits developers to use their own programming style to resolve different issues. They can choose from the imperative, functional, object-oriented, and procedural styles to meet their purpose. This feature of the programming language reduces the occurrence of errors by providing complete control to the programmers.
Codes written in Python are easy to understand; it means any developer can change or edit it without the help of the one who developed the application using this language. This helps AI and ML professionals to exchange algorithms, tools, and ideas without any confusion or conflicting paradigms.
- A plethora of visualization options
Python’s huge numbers of libraries are excellent visualization tools. Some of its libraries (including the most popular one Matplotlib) permits the data scientists working on AI and ML applications to create plots, histograms, and charts for clear data comprehension, understandable presentations, and visualization. Apart from this, Python has a variety of APIs to simplify the complete process of visualization to create better reports.
- Can run on multiple platforms
Python, when used for ML development, offers complete platform independence. It means the developed app or the software can run on Linux, Unix, macOS, Windows, and other platforms. Merely by making small changes and edit a few codes, the developer can make the code ready for other platforms. To prepare this new executable form of code, the developers can use PyInstaller.
- Big library ecosystem
Python offers a wide array of libraries, which makes it a perfect choice for AI. A library contains a pre-written piece of code using which developers can attain different functionalities and perform various actions. These libraries also prevent the developers from writing codes right from the scratch, which reduces a lot of time and effort. Some of the popular Python libraries that can help in AI and ML app development are:
- Matplotlib
- Scikit-learn
- Pandas
- NLTK
- Keras
- Caffe
- TensorFlow
- PyBrain
- StatsModels
- Python has low entry restrictions
When you develop applications using AI and ML, it is clear that you would be working with a large volume of data, which further needs to be analyzed and processed. Python’s low entry barrier feature permits data scientists to quickly choose Python and start working with it. In other words, you don’t need to put efforts into learning the programming language. Its syntaxes can be written in common English, which makes it a beginner-friendly language. Moreover, the language also permits you to work with complex systems without any hassle.
Let’s have a look over the case studies where Python has been used as a programming language for AI and ML:
You already know that the programming language, we are talking about in this article, offers ample of benefits for AI and ML, but, let’s make your belief stronger with these use cases:
- Healthcare
- Fintech
- Transportation
- Travel
Healthcare
AICure and Fathom are the two AI-powered projects that have been developed using Python and helping the healthcare industry with different advantages such as face recognition, pill recognition, analyze health records of the patients, and more.
Fintech
Venmo, Robinhood, and Affirm are some of the successful Python-based software that helps users to control purchases and payments along with creating a social network to allow people to stay connected in the app/software.
Transportation
An ML-based platform named Michelangelo PyML has been developed by Uber by using Python. The software helps the company to make offline and online predictions.
Travel
Skyscanner, a big name in the travel industry, utilizes a Python unsupervised algorithm to forecast the behavior of new routes for the airplanes.
Final words
AI and ML experts worldwide are using Python as a preferred language for developing applications powered by artificial intelligence and machine language. This article covered up the top five benefits that the language renders to the programmers. To know more about how Python is used to develop AI and ML-powered apps, reach out to a reliable Python development company, or hire Python developers.
