Introduction
Python is considered the best programming language because its simplified syntax focuses on Natural Language. Writing and executing codes has become much quicker and easier with mainly with Python for AI and ML.
The purpose behind the invention of Python was to build a general-purpose language that doesn't specialize in solving a specific problem but focuses on building diverse programs. Python is used frequently for building websites and software, automating tasks, and conducting data analysis. The recent use cases on Python indicate the widespread use of Python for Artificial Intelligence and Machine Learning.
Why Python for AI and ML?
If you are already familiar with Python, you must be aware of its strength in pattern recognition and predictive analytics; however, Python for Artificial Intelligence (AI) and Machine Learning (ML) is not the only language preferred. Then, why is Python the best for Artificial Intelligence, Machine Learning, and Data Science as well?
Here are some of the most effective Python features that make it best to use Python for Machine Learning and Artificial Intelligence.
1. Better Library Ecosystem and Frameworks of Python
There are more than 137,000 libraries in the Python programming language and mainly three types of Python frameworks;
Full-stack frameworks- Full-stack doesn't require a specific introduction. Python Full Stack frameworks like Django, Web2py, TurboGears, and CubicWeb are considered vital frameworks in Python.
Micro-framework- These minimalistic frameworks are not full-fledged. Some of their functionalities are missing, which are common in other frameworks. Still, it has vital features for AI and ML services with Python.
Asynchronous- Asynchronous in Python provides a high-performance network, web servers, data connection libraries, and distributed task queues.
2. Simplicity of Python
Simplicity is the crucial feature that distinguishes Python from programming languages like C, C++, and Java. Python rarely disallows something. By that, designing irregular programs to solve the straightforward issue is easy.
3. Flexibility of Python
Python is considered the most flexible programming language as solving a precise problem was not the purpose it was created for, and Python is well-suited for quick development of all kinds of applications as APIs or templates do not drive it.
4. Readability of Python
In Natural language like Python, the readability of text relies heavily on its content which is determined by the vocabulary and syntax used in the text. It emphasizes the vocabulary the developer chooses and how they use it to form a sentence making it easier for the reader to read and comprehend.
5. Popularity of Python
Python is the first choice for many developers for web development, data analytics, machine learning, data science, and artificial intelligence. Companies like Google, Facebook, Instagram, and Netflix depend on Python for AI and ML to a major extent. These kinds of big companies prefer to hire in-house ML engineers but it is advised for small and medium-sized companies to take the help of outsourcing companies to hire Machine Learning engineer or leverage the knowledge of AI consulting.
The Popularity index PYPL is updated every month. In June 2022, Python had the highest of 29.53% and was the first in popularity, followed by Java with a 17.06% popularity index.
6. Less Coding of Python
The results are the same, with fewer lines of code and even better accuracy. The less the amount of the code, the lesser the bug count will be with more readable and maintainable source code.
7. Quick Execution with Python
The code can be executed as a script using the command line and importing the python code from one file to another or into an interactive interpreter.
8. Better Visualization with Python
For better visualization in Python, developers use various data visualization modules such as Seaborn and Matplotlib. As Python is easy to learn, developers may not face trouble while integrating Python into the data visualization system.
9. Community Support of Python
Millions of developers using Python in the global community of Python programming language remain in touch online and offline to support each other with issues being faced.
10. Platform Independence of Python
As Java programs can be run on different platforms with the help of JVM, Python programs can also be run on various platforms with the help of an interpreter built for that platform.
11. Fast Development with Python
Python allows very quick prototyping speed as an interpreted and dynamically typed language. That has increased the hype about AI and ML development and organizations hire AI engineers who can work with Python to give them quick and the best resolution.
Other programming languages for AI
Undoubtedly, Python is the most appropriate choice for Artificial Intelligence development, yet it is not the only one. Here are a few other programming languages widely used for AI development.
- Java
- R
- C++
- Julia
- Lisp
Other programming languages for ML
Regarding programming languages, Artificial Intelligence and Machine Learning share common languages with fewer or more features for specific technologies. Here is the list of programming languages considered for Machine Learning apart from Python.
- R
- Java
- Lisp
- Scala
- Typescript
Programming languages for Data Science
You may see a couple of new programming languages in Data science as the technology is slightly different from those mentioned above. So businesses are advised to recruit data scientists who are well versed in at least one of the following languages.
- R
- SQL
- Java
- Julia
- Scala
Conclusion
Although Python is not the only language, developers widely use it for Artificial Intelligence and Machine Learning, with the highest share of users. Python for artificial intelligence and machine learning makes the tasks easy with its natural language processing capabilities.
Along with AI and ML, Python is also very useful for Data Science. Python and R language are profoundly used in the domain of Dataverse. I would recommend you to read more on Python vs R, if you are keen reader of the latest technology blogs.
Simplicity, consistency, accessibility to its libraries and frameworks, flexibility, global community, and platform independence are the most important features that make Python the best fit for Artificial Intelligence and Machine Learning projects.
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