Artificial intelligence and the many subsets under its umbrella continue to contribute to the way that businesses evolve their operations and processes. Most specifically, machine learning has paved the way for a number of some of the most unique advancements we see in our everyday lives. What shocks the most people is that most of these machine learning processes are done by computers themselves, with no programmer intervention. Without any explicit coding needed, these programs, through the analyzation and interpretation of data, are able to learn and identify possible solutions for companies around the world. This post will detail the ways in which this is made possible, in addition to the ways your business can fully utilize these technologies.
It can be difficult for any average user to identify how a business and their applications operate. However, when they notice a new feature that they think adds value to their experience, it’s more than likely birthed as 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. Facebook’s suggestion will likely connect you to more similar friends, just as Instagram would. In the retail space, Amazon users may receive product recommendations on a regular basis based on their 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.
What many users fail to ever think about is how any of this is accomplished. Reasonable, as most of these tools massive amounts of data to be built out and remain functional. 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. But what about the development processes of these technologies? How are they accomplished? Typically, programmers will utilize Python as their primary language.
Machine Learning and Data Science applications being built on Python is a very common trend due to its ability to fluently work with large amounts of data. Its strengths don’t stop there, with a straightforward syntax, the inexperienced programmers are often taught Python as their first language, which means it has some staying power. Not only are more programmers familiar with this language, but for those that prefer working on a different operating system or with a different programming language when necessary, Python is particularly flexible and compatible, making it the perfect choice for these situations. Couple this with its open-source nature, there are also an extensive number of online libraries that include large amounts of pre-written code able to be integrated into any project.
What many businesses fail to realize is that developing these technologies takes a significant amount of time. There is likely no chance for your business to suddenly shift all of its efforts into these machine learning tools without the right level of preparation. Luckily, with the help of the right partner and their Python Data Science Training courses, your business could transform its machine learning efforts. For more information on how these courses work and the strengths of Python, be sure to continue reading on to the infographic paired 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.
