Python’s Contribution to Machine Learning & Data Science

The way many companies and organizations around the world have utilized different artificial intelligence applications in their operations has changed drastically over time. One of the most common applications that these businesses have turned to is Machine Learning, a form of artificial intelligence that possesses a method of autonomous learning. Meaning that these programs are innately learning through the data that businesses are inputting into them. This is no easy task, but one particular programming language makes the challenge a bit more manageable: Python.

There are a number of reasons why Python is the preferred programming language of choice for Machine Learning applications. The first is that it’s one of the easiest programming languages to use as it has such straightforward syntax. This language is often one of the first languages that aspiring programmers are taught, indicating its ease of use and thus how little amount of time has to be spent in order to feel comfortable with the language. The more comfortable a programmer feels with Python, the sooner they’re able to begin working with the large amounts of data they’re meant to analyze.

If that weren’t enough, Python also possesses a number of extensive libraries that include prewritten code for a number of functions and actions available to be used in any project. This saves a great deal of time for programmers as they no longer have to program base level code from scratch. Some of the libraries utilized include Numpy, Keras, PyTorch, Pandas, Theano and many more. In addition to this prewritten code, these libraries often include data representation tools such as integrated charts and histograms to allow for a more visually appealing presentation of the data programmers are working with.

In addition to these resources, Python is one of the most flexible programming languages that can be used for these applications. Programmers have more options when working with Python in this case as it is able to be combined with other languages in order to reach the desired result. For example, Python is able to be used on all major operating systems. Unix, Linux, macOS, Windows, whichever is preferred or necessary for the task at hand. Alternatively, if you’ve been working on a process you need to transfer over to another platform, not a problem. Some simple modifications of the code will ensure that it will run just as smooth on the new platform.

Perhaps the most important reason as to why Python is the language of choice for these Machine Learning applications though has to be its usefulness in data science. The process of drawing information and insights from the data collected by businesses regarding their customers are able to be turned into strategies when properly utilized. This is where Python shines. For more information regarding the advantages of Python in the Machine Learning space, be sure to check out the featured infographic below.

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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