Evolutions Of Machine Learning Made Possible With Python

More and more advancements to the ways in which businesses operate are being discovered as a result of the use of Artificial Intelligence and Machine Learning. Many of the most famous functions found on the applications we use every day are thanks to AI and ML. But how is any of it accomplished? Through the use of machine learning, AI is capable of learning all on its own which in turn can help organizations identify, analyze and solve a number of their most unique issues. This post will detail a number of the ways in which this is possible and include a breakdown of how it’s accomplished.

As previously mentioned, many of the things that people love today are a result of machine learning. For example, Instagram users will be shown recommended content or accounts to follow based on their account’s activity and followed users. This can also be seen through Facebook’s suggestion of recommended friends based on similar connections that you and the suggested friend might have. Or in the case of Amazon users, you may receive product recommendations on a regular basis based on your most recent purchases. Believe it or not, there are also even more complicated services offered as a result of Machine Learning. For example, automated fraud detection from your banking provider is made possible through Machine Learning. Similarly, translation services, and even predictive text finishers on your phone are a result of python-powered machine learning applications.

It can be difficult to understand how all of this is accomplished if you’re unfamiliar with the process. In order for these applications to be developed, it requires a massive amount of data. Programmers then develop code meant to interpret and analyze this data in order to provide business insight that companies are able to use to develop strategy meant to take hold of a competitive advantage in their space. These developments also enhance the user experience as mentioned previously. But what is the most common programming language to accomplish all of this? Python.

Python has become the premier programming language for these types of highly data-sensitive operations. Artificial Intelligence, Data Science, Financial Services, you name it. Anything that requires working alongside large and consistently changing data sets is the ideal situation for utilizing Python. Due to its straightforward syntax, community support including extensive libraries of pre-written code able to be utilized for free, in addition to its flexibility to work in connection with different programming languages make it the best choice for these projects.

While these advantages make it clear as to why Python is the most common choice for programmers working with Machine Learning and Data Science applications and projects, the list goes on. If you were hoping to learn more about these advantages, please consult the infographic shared alongside this post, Python Programming & Its Importance In Machine Learning. Or, if your organization is interested in how python can positively contribute to internal processes, consider looking into Online Python Training Courses.

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.