An Evaluation Of Python’s Impact On Machine Learning

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As our understanding of artificial intelligence and its capabilities have evolved, so too have the ways in which we’ve been able to benefit them. While most benefits are seen at an industry wide level, there are some improvements that have been made at the individual level for those living their everyday lives. Of the most impactful, machine learning specifically has paved the way for a number of the massive improvements made across the world. When these programs operate accordingly, they give computers the ability to learn on their own and develop insights from what they learn. If you were interested in the way in which this comes about, specifically learning about Python’s involvement with the development, be sure to continue reading on.

As mentioned above, Python continues to be the language of choice for programmers working alongside different machine learning projects. While other programming languages have their place, Python seems to be the favorite. The reasons why that is? The first would be 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.

Another reason in which it is used so frequently is the fact that it accelerates the workflow of the programmers working with it. Through the use of code offered from an extensive list of community libraries, programmers can reference and use base level code rather than writing it themselves. Libraries such as TensorFLow, Theano, scikit-learn, and others, provide these functions as well as different data interpretation tools for programmers to more efficiently work through and display the insights they derive from the data they’re provided.

While its community support certainly simplifies any of the challenges a programmer can have, it’s also flexible enough to work alongside different languages or operating systems when necessary. 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.

Not only is machine learning work largely impacted by Python, but a majority of data science work is accomplished through the use of Python as well. Its ability to identify pertinent information and derive insights from this information can make all the difference in the ways in which organizations go about acquiring a competitive advantage. For more information on how this is accomplished, or how your business can benefit from third-party offered Online Python Training Courses, be sure to take a minute 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.