How Python is Utilized in Machine Learning & Data Science Applications

Artificial Intelligence and its vast capabilities have changed the way businesses operate today. One of the major applications that is utilized to develop business strategies today is known as Machine Learning. Machine Learning is a form of Artificial Intelligence that allows computers to innately learn and interpret data without any sort of programmer intervention. This creates a number of opportunities for businesses to prosper and is made possible through the use of Python.

But why Python? Python’s popularity amongst Artificial Intelligence and Machine Learning Applications is due to a number of reasons. The first reason is that it’s a rather simple programming language to use and learn. This is in part due to its straightforward syntax, meaning it’s not a difficult language to read and understand. This allows programmers to get a grasp on the concepts and develop a strong foundation with Python and are immediately able to begin working with the data they’re presented with for their AI and ML projects.

Python’s ease of use is made even more clear when considering the numerous amounts of established libraries full of prewritten code for base level functions and actions that programmers can easily extrapolate for their AI and ML projects rather than developing this code from scratch each time. Some of the most popular libraries include: Keras, TensorFLow, scikit-learn, in addition to many others. These libraries often include additional functions such as data representation tools like charts or histograms in order to more properly visualize the analysis they’ve worked through.

If its ease of use wasn’t enough, Python is also one of the most flexible languages for these applications. Programmers have the freedom to combine whatever programming styles or languages they’re most comfortable with in order to complete their projects. In addition to this, Python is easily utilized on all major operating systems (Linux, macOS, Windows, etc.) If a programmer has been working on a project that requires a platform switch, that is made possible through some simple modification of the code.

These are just a few of the reasons that support Python’s claim for the most suitable language for data science applications. For more information on why it’s so popular, be sure to check out the featured infographic below. In it, you’ll find additional information regarding Python and its usefulness in Machine Learning applications.


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 and works on various projects to promote the business. 

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