The reach that Artificial Intelligence poses today will only continue to extend as time goes on. Meaning the ways in which it will integrate into everyday life will continue to extend as well. A particular subset of Artificial Intelligence that has seen significant growth in recent years is known as Machine Learning. When executed correctly, this allows computers to learn and identify trends through the analyzation and interpretation of data. The benefit of Machine Learning is that this can be accomplished without any programmer intervention necessary. It’s through these systems that companies worldwide are able to determine ways in which they can both serve their customers’ interests and their own businesses’ interests simultaneously.
Believe it or not, Machine Learning has also paved the way for a number of improvements that have changed the way individuals use different applications. Instagram users, for example, benefit from recommended content and accounts to follow via their integrated explore page. Something similar has been utilized by Facebook as well, as they have a suggested friends function that is predicated on different connections users have already made on the platform. In the case of online marketplaces, such as Amazon, customers will see tailored product recommendations based on previous purchases, indicated product preferences and more. Even some of the most integral safety functions offered by banks nationwide are powered by Machine Learning. Automated fraud detection is the perfect example. Some advancements have even been made in the way that translation services operate as a result of Machine Learning.
Just how are all of these applications made possible or available, though? None of these advancements would be possible without massive amounts of data. Data collected from organizations around the world is assessed and broken down by code developed by programmers. This code breaks down the numerous collections of data into meaningful interpretations that allow organizations to form a competitive advantage. The programming language most commonly used to accomplish this is Python.
Python’s ability to work so effectively with large amounts of data is what makes it the preferred language of choice for these Machine Learning and Data Science applications. Coupled with its straightforward syntax, it is both beginner friendly and able to be understood in a meaningful way by even the most unexperienced. Python is also immensely flexible, giving programmers the freedom of using different languages when necessary and even remaining functioning whilst exporting their work to different operating systems. Its compatibility makes this possible and its open-source nature makes for a great deal of resources to be available to programmers. Some of these resources include online libraries containing massive amounts of pre-written code able to be used freely by any programmer, saving them countless amounts of coding hours.
These types of advantages are what allow Python to stake its claim as the most effective choice for programmers working in the Machine Learning and Data Science space. If you’re looking for more information regarding Python and how it relates to Artificial Intelligence development, be sure to check out the infographic accompanying this post. For an even deeper dive on the subject, consider a set of Online Python Training Courses focused on this relationship.
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.
