In order to understand why Python is important in Machine Learning, it’s necessary to know the definition of Machine Learning. Machine Learning is the development of programs that grant computers the ability to learn from large amounts of data without being explicitly encoded. This process applies to a wide range of applications around the world, including the personalized product recommendations you see online and the spam filters that prevent your inbox from being flooded.
In order for a system to learn automatically, however, there is extensive work that must be done on the backend. The programming language of choice for most AI and Machine Learning applications is Python, and here’s why.
Primarily due to its ease of use and ability to work with large amounts of data, Python is often one of the first languages that aspiring programmers are taught. It has become a standard for large-scale applications such as artificial intelligence, data science and financial services. In addition, Python has a straightforward syntax and is easily integrable with other languages.
Furthermore, Python’s flexibility allows programmers to have more options when working toward a goal. For example, Python is compatible across various operating systems such as Unix, Linux, Mac and Windows. In addition, Python’s comparability with languages such as C and C++ allow for more and easier techniques to reach a desired result.
Most important, however, is Python’s extensive libraries and toolkits that provide base level code. Using Python, you don’t have to waste time with rudimentary programming tasks. Some of these libraries include pandas, TensorFLow, PyTorch, Theano, Apache Spark and more. They also consist of tools that create simple visual interpretations of the data with which they work.
Finally, and not to be forgotten, is the community support that Python programmers often supply. As it is an open-source language, there are a large number of free resources scattered about that allow programmers to ask and answers questions, discuss various applications and work opportunities, and aid one another.
For more information on the advantages of Python in Machine Learning and its many applications, check out the accompanying resource, courtesy of Accelebrate.