Why Python is Good for Artificial Intelligence: The rise of Information Technology in the 21st century can be attributed to the development of various software and hardware systems. Programming languages like JavaScript, C, C++, and many others are working wonders in the domain of software development.
Among others, Python is one such language that has gained traction and doing wonders in the development sector. Because of its easy-to-interpret and code- syntax, the range of libraries it offers, flexibility, and many other factors, Python has become a go-to language for developers working on Artificial Intelligence projects.
The application of AI to develop programs that do human-like jobs and portray human skills is Machine Learning. Both Artificial Intelligence and Machine Learning are closely connected and are being used widely today.
While these programming can be done using several languages, developers mostly prefer Python for this purpose. Python is an open-source language with a huge backing of the community. There are some features that make Python stand out among other programming languages. Even the Python Web Development Services are readily available in the tech world today.
Having said that, let us discuss some features of Python that makes it the best choice for Machine Learning and Artificial Intelligence-
10 Best Reasons Why Python is Good for Artificial Intelligence and Machine Learning
1. Libraries
Python offers a plethora of libraries that assist programmers accomplishing their objectives. Libraries are modules containing pre-written codes and functions that can be reused to define new functions, which otherwise would have required tedious coding work. For the purpose of Machine Learning, Python provides several libraries like SciPy, Scikit Learn, TensorFlow, etc., that help developers read and transform data, and to develop decision-making algorithms.
2. Readability
Python Codes are easy to read by the developers. The coding structure is coherent and the indented structure makes for a neat programming structure. Ambiguity is very less and therefore it becomes convenient for developers to read programs and necessarily explain them to their peers. Moreover, there are several IDEs and tools available for Python, which provide testing, debugging, and auto-completion features that make the programming process more convenient.
3. Syntax
Python syntax structure is very coherent and the language is quite simple. The syntax for working with data types, functions, methods, and classes resembles general English and hence can be easily comprehended. The programming flow of a Python program is very coherent due to the indented structure of codes. This helps avoid ambiguity and confusion among readers.
4. Easy to learn
Machine Learning and Artificial Intelligence is something that is more likely to be pursued by a scientist or an algorithm expert. Usually, most of these professionals aren’t as experienced in general programming. Python language- being easily understandable due to its simple coding language and comprehensive syntax, makes it easy to learn and work with, without one being highly experienced.
5. Flexibility
Python is user-friendly as the coding done doesn’t need to be compiled every time a change is made, unlike as in C++. This helps programmers to quickly edit the code and see the results if such requirements arise. Moreover, programming in Python can be done as per OOPs or Scripting basis. Programmers can also choose an imperative style programming or a functional style, if they want to adopt, thereby offering flexibility.
6. Independence
Apart from offering flexibility and comprehensive syntax, Python also offers coding flexibility when it comes to operating platforms. Programmers can develop working on any platform, be it Windows, macOS, Linux, Unix, or 21 other platforms that Python is compatible with. When it comes to transferring data from one platform to another, programmers can use PyInstaller or other similar packages that would render the code in accordance with the relevant platforms.
7. Visualization
Visualization is an important aspect when it comes to Machine Learning, Artificial Intelligence, or Data Science. This is because the data needs to be represented in a human-readable format. Python provides libraries that help represent data in the form of charts, graphs, and plots. Matplotlib and Plotly are a couple of libraries that offer such functionalities.
8. Big Data
One thing that ML and AI developers have to inevitably deal with is data. To develop a reliable algorithm or application that works on Machine Learning, the developer has to develop a reliable decision-making model for which a lot of data is generally required. For efficient programming, the programming platform needs to support this data, and Python can do that seamlessly.
Apart from being efficiently compatible with SQL, Python offers several libraries like Dask and Pyspark that can help handle and process big data seamlessly. From the Pydoop library, developers can process data from the HDFS cluster. Python can also be used for Hadoop using parallel computing.
9. Community Support
A major advantage of Python is that it is an open-source programming language. Over time, since its inception in 1991, it has emerged as a very resourceful language that offers several features for general-purpose programming. For this reason, the number of programmers that rely on Python is huge. This community not only reaps the benefits that come up with Python updates but also is responsible for several libraries and frameworks that have been introduced to public use.
10. Popularity
Python is one of the most used programming languages these days. This has been possible due to it being an open-source platform and the immense programming possibilities that it provides to its users. For any programming field, there are many libraries available that can be used to develop interactive applications or utilities.
Several big companies rely on Python to run their applications. The list includes Netflix, Dropbox, Google, Spotify, and so on. The use varies from Machine Learning, APIs, and web applications. The popularity of Python ensures the presence of professionals who can reliably do the required job at a reasonable price.
Conclusion
Python is a popular language for general programming and in recent years, its popularity has grown significantly as an ML programming language. If you are planning to pursue a career in Machine Learning and Artificial Intelligence, you will certainly come across this subject. The field is still developing and so is the language. Yet, it is the platform that is widely adopted and considered the best when it comes to ML and AI programming due to the above reasons.
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