As more and more companies begin to adapt to the new technologies birthed out of artificial intelligence, more and more possibilities open up; This applies to both organizations as a whole in addition to customers. The most obvious example comes in the form of machine learning, a subset of artificial intelligence known best for its ability to learn autonomously. With these programs, organizations are able to learn from the work done by these systems. This work is predicated on the data that businesses are collecting from their customers. While complex in nature, most often these programs are developed with the help of the Python programming language.
What makes Python such a popular choice, though? First and foremost is Python’s simplicity. With such a straightforward syntax, the basics of the language are easily picked up on. For programmers new to the language, this can be an excellent leg up compared to other languages they may be well versed in. With the ability to pick up on the language quickly as a result of its simple nature, programmers are able to begin developing these machine learning algorithms much quicker compared to other languages.
Wondering how all of these advantages are made possible? Without massive amounts of data to support programmers, none of it would be possible. Data collected from organizations around the world is assessed and broken down by code developed by programmers. This code breaks down the numerous collections of data into meaningful interpretations that allow organizations to form a competitive advantage. The programming language most commonly used to accomplish this remains Python.
Its simplicity is a huge advantage, but perhaps even more important than its simplicity is its compatibility. Programmers working with any project including Python can use whatever language they’re most comfortable with due to its compatibility. Further strengthening its compatibility, Python is able to work across the most common operating systems used today. Windows, macOS, Linux, etc. In addition to this, programmers working with Python can rely on online libraries filled with base level code that is free to use. Some of these libraries include Keras, pandas, TensorFLow and scikit-learn.
While this post serves to provide a good foundation of understanding for those unfamiliar with Python, there’s still a lot to learn. For more important information regarding this programming language and how it relates to Machine Learning and Data Science, be sure to review the infographic paired alongside this post. Additionally, if you believe your organization could benefit, consider looking into Online Python Training Courses from certified professionals.
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.
