Prepped By Python – Data Science Improvements Powered By Python
As more and more businesses look to identify ways in which they can continue moving the needle forward, artificial intelligence and its many technologies and offerings are the clear favorite. Businesses, most specifically with machine learning, are able to provide some insane advancements and improvements to their offerings, especially related to their mobile apps. With the help of autonomous learning computers, businesses can better process data and derive insights that positively contribute to their bottom lines. This post will detail these advancements, in addition to the programming language of choice for most of these projects, python.
Python is the preferred programming language for these machine learning projects for a few reasons. First and foremost, Python possess a simple and straightforward syntax. Meaning it’s one of the easiest languages to understand even without any level of familiarity with it. Which is why it’s so commonly taught as the first language for many aspiring programmers around the world. Knowing that mastery isn’t required in order to begin working with the data these systems are meant to interpret, it becomes an easier language to pick up on in a short period of time.
Another innate aspect of Python that makes it so popular in developing these applications is its community support. This support can be seen through the extensive list of existing free libraries full of pre-written Python code for programmers to utilize. These libraries include: TensorFLow, Theano, scikit-learn, and others. Each of these provides programmers with base level functions easily integrated into their work in addition to different data interpretation tools for programmers to more efficiently work through and display the insights they derive from the data they’re working with.
In addition to providing its users with such immense support, Python is arguably one of the most flexible programming languages used today. Being compatible with other languages like C and C++, along with its ability to work across a wide suite of platforms and operating systems (macOS, Windows, Linux, Unix, etc.) illustrates its flexibility. This ultimately gives programmers a sense of freedom in programming where and how they prefer when working through any project.
Circling back on its community support, programmers around the world often contribute to online forums or platforms that are in place to help other programmers working with Python. This is similar to the free libraries mentioned previously. This sort of community is incredibly beneficial for developing machine learning applications. However, for businesses hoping to find the value in these python-powered tools, they may need some assistance that goes beyond community support. In those instances, businesses often invest into Python Data Science Training courses from a partner to be better prepared for what’s ahead. To learn more about Python and these courses, be sure to continue reading on to the infographic included 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.
