How Machine Learning Is Impacted By Python Programming
As the COVID crisis continues to ravage on, more and more businesses are looking for ways to achieve a competitive advantage within their industry. With the technologies having evolved in recent years, artificial intelligence tends to be the direction these businesses head toward. One application of AI in particular, machine learning, has proven to be very valuable within the business sphere. Through unique python powered systems, machines are capable of learning autonomously. Of course, they’re only able to do so when provided with an ample amount of data. Throughout this post, a breakdown of how these systems operate and the ways in which they’re supported will be detailed.
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.
While all of these services are great, there’s more to be offered from Python. In fact, most would argue that the most beneficial aspect of the language is the pre-existing libraries full of pre-written code for programmers to implement and utilize when necessary. TensorFLow, Theano, scikit-learn, and many more, provide base level functions ready to be integrated into whatever project a programmer is working on. So, rather than having to spend the start of each project fleshing out the basics, they’re already provided. An effective head start, if you will. In addition to this pre-written code, these libraries also offer programmers free tools meant to better graphically represent the data they’re working with, as well as the analysis that they conduct.
Not only is this language particularly simple, it is also notably compatible and flexible amongst other languages. Meaning programmers can use Python if they’re most comfortable with it, or they can stick to their default language and use Python when necessary. Combining styles is not as difficult as some might think. In addition to this, Python is compatible with the most common operating systems used today. Windows, macOS, Linux, etc. So if you need to move your project to a new operating system, fear not. Transferring your work is as simple as modifying a few lines of code.
Strong community support is what rounds out all of the benefits that Python receives as a result of its open source nature. In fact, there are even Online Python Training Courses available to aid businesses in need. With all of these capabilities, its work in the Machine Learning & Data Science aspects of many businesses worldwide are able to provide immense value. If you were hoping to learn more about this programming language, or the many ways in which it is utilized, you may want to check out the infographic featured 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.