Why Python Is The Premier Programming Language In Machine Learning Applications

While artificial intelligence (AI) may include an extensive set of applications that assist us in our daily lives, not many understand how these tools are developed. This post will highlight one of these tools, machine learning. Machine learning is a type of AI designed to allow for computers to learn on their own. In other words, without requiring explicit direction from a programmer. This type of AI has become common across a majority of all major industries for its ability to identify relationships between the large amounts of data input it receives. The most common programming language for Machine Learning and other AI applications is Python. 

There are a number of reasons that Python is the preferred programming language for many Machine Learning applications. The first being its simplicity, both in learning and syntax. In fact, this is often one of the first languages that novice programmers are instructed to learn. It certainly isn’t something to scoff at, but it takes much less time to learn so programmers are able to jump right into the code and begin working through the data they’re supplied. 

Building off its simplicity, there are a number of external resources that make Python an easy choice for the development of many ML projects. These resources, which are online libraries of prewritten code, serve to provide programmers with a number of functions and actions they are able to implement without having to develop them with their own time. Base level code no longer requires the time to develop due to these resources. Some of the common libraries include pandas, Keras, TensorFLow, scikit-learn, and others. These libraries also include data representation tools that allow for more visually engaging pieces to present insights found through data analysis. 

If libraries full of prewritten code weren’t enough, the additional community support Python receives is not to be understated. Due to its open-source nature, these libraries aren’t the only free resources you’ll find in a search for help with projects. Plenty of communities exist that allow programmers to ask questions, discuss different issues, and provide help when necessary. 

In addition to its ease of use and reliable community support, Python’s flexible nature allows for more ways to integrate alternative languages to solve problems. The same can be said for the operating system you’re currently running on. For example, if your platform currently runs a macOS, but you need to complete the remainder of the work on Windows, modifying a few lines of code will make the transition much simpler than many would think.   

For these reasons, amongst others, Python proves to be the most suitable language for data science and machine learning applications, ss both of these fields require identifying pertinent information and insights from input data in order to develop business strategies. To further understand how Python shines in these applications, check out the infographic below. Courtesy of Accelebrate.