The impact that Artificial Intelligence possess over a number of businesses and their most critical functions continues to increase. Some of the functions of these businesses influence the ways in which peoples’ everyday lives are impacted as well. A particular subset of Artificial Intelligence that has seen significant growth in recent years is 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.
A majority of the most popular features on social media are a result of machine learning. For example, think of how many social media platforms that have some form of user recommendation. Facebook friend suggestions, Instagram account recommendations, a ‘Twitter users you might know’ section. Data used by machine learning algorithms are responsible for these suggestions. The same can be said for any online web-store product recommendations. Amazon, Walmart and the all other major online retailers utilize machine learning to provide the most personalized experience for customers. Even more complex work is accomplished through machine learning. Take the fraud detection services from any major banking provider for example. All of these and more are accomplished through python-powered machine learning programs.
But just how are these programs developed? How are they supported? First things first, none of this would be possible without enough data. The constant collection of pertinent data is of utmost importance to making these programs successful. Once data collection is settled, programmers can develop code focused on interpreting and analyzing the data and translating it into actionable insights. These insights are then used to develop the business strategies meant to provide some form of competitive advantage for these organizations. The organizations that struggle with this discipline often look to Online Python Training Courses as a means of learning more about how these services can improve their effectiveness.
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.
Python’s popularity doesn’t end there, though. There’s still a lot more information regarding its importance in machine learning to be discovered. For more of that information, be sure to check out the infographic coupled alongside this post.
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.