Organizations around the world have begun adapting to Artificial intelligence (AI) as a result of the competitive advantage it has provided for countless industries. There are countless amounts of industries that benefit from Artificial Intelligence and its wide suite of applications. One of the most influential applications of AI today is machine learning (ML), a form of AI that allows computers to learn without being explicitly programmed. This autonomous learning is accomplished without programmer intervention. That’s not to say no coding is done for these applications, in fact it’s quite the contrary. Most programming done for these applications is done with Python.
There are a number of clear-cut advantages to Python in the development of these applications. Most notably, is its simplicity. Python is a programming language with a particularly straightforward syntax. Which means it requires less time for beginners to gain a comfortable understanding of the basics and allows those working on AI and ML projects to immediately begin programming and processing large amounts of data.
Its simplicity is only made more clear by the collection of extensive libraries available online that include basic prewritten code for certain functions and actions ready to be used. That means programmers can import Python’s base level codes without having to code them from scratch. Some of the libraries include pandas, Keras, TensorFLow, scikit-learn and many more. In addition, these libraries provide the programmer with data representation tools such as charts, histograms and other visually appealing pieces that can make presenting insights and conclusions more engaging.
If these preexisting libraries weren’t enough, Python’s flexibility yields even more possibilities for programmers. Programmers have the ability to choose the programming style with which they are most comfortable — even being able to combine programming styles in conjunction with other languages to reach their desired result. One example of this is Python’s ability to function on diverse platforms and operating systems including Unix, Linux, macOS, Windows and others. If you’ve been working on a particular operating system and you need to transfer to another, all you have to do is modify a few lines of code to make sure everything will remain compatible on the new operating system.
Circling back to its simplicity, Python is also an easy language to read and thus easier for beginners to understand what the code means as well as copy and change it, if necessary. Beginners are also met with a strong sense of community support. Python is an open-source language which means there are numerous external resources that Python programmers use to ask questions, discuss issues and help one another all free of charge.
It’s hard to deny the capabilities of Python when it comes to data science applications. In fact, it goes even deeper than what this post has covered. For more information on the relationship between Python and these various applications, be sure to check out resource accompanying this post. It does a great job of highlighting some additional advantages that Python possesses and how it’s used in AI applications around the world.
Author Bio: Anne Fernandez – Anne joined Accelebrate in January 2010 to manage trainers, write content for the website, implement SEO, and manage Accelebrate’s digital marking initiatives. In addition, she helps to recruit trainers for Accelebrate’s Python Training courses and works on various projects to promote the business.