Reasons Developers Think Python Is the Best for AI
Reasons Developers Think Python Is the Best for AI
Let's take a quick look at some reasons why developers think that Python is the best for Artificial Intelligence.
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AI has gained a lot of prominence and identity in ensuring proper data security. This theory enables machines to perform human-like tasks, which in turn forms a critical infrastructure in aiding data security. Artificial Intelligence based cybersecurity products have been proven to accelerate incident detection, incident response, identify risk factors, and create a situational awareness. Artificial Intelligence-based devices are sure to take over the next level of cybersecurity process very soon as they add more efficiency and value to the entire process.
Over the years, developers have used several coding languages to develop AI-based applications. For example, Java, LISP, Prolog, and C++ fall under the category of widely used languages for an AI-based application. However, in addition to these, developers have also used Python for a number of applications, which include General AI-based application, Machine Learning, NLP, and Neural Networks. What makes Python the preferred choice amongst developers compared to the other equally dependable languages? This article sheds some light on the specific reasons from a developer’s point of view.
Where Python Scores
The choice of any programming language always depends on how robust the end application is desired to be. In addition to this, the complexity in coding and the availability of an experienced developer also has an important role to play. Python, being an OOP (Object Oriented Programming)-based programming language and focusing extensively on RAD (Rapid Action Development) and DRY (Don’t Repeat Yourself) contributes immensely in developing robust applications by quickly adapting to changes and eliminating duplication of logic. This is not all that Python as a language is capable of. Read on to know more.
A Developer’s Choice for AI Projects
Python is known to support multitasking. Irrespective of the magnitude of a business establishment, whether small or big, Python, as an OOP, facilitates performing multiple tasks at the same time.
Python brings with itself the advantage of having built-in libraries which is extremely useful for any AI-based project development. With the presence Internet protocols such as string operations, web services tools, and operating system interfaces being some of the key components of these libraries, Python saves on time by reducing the length of the code required for developing an AI-based application.
Amongst the prominent highlights of Python, as a programming language, has been its readability. Though there is a lot of innovative technology, associated with AI (Artificial Intelligence), the ease of testing provided by Python makes it one of the most preferred programming languages, compared to either a C++ or even a LISP.
As a user-friendly coding language, Python provides the developer, with a flexibility, to easily write and execute all the codes. Where Python stands out with respect to other languages is with its ability to produce the same, even better results, compared to its competitors, with the practically lesser amount of coding required.
A flexible programming language like Python is also a new developer’s delight, especially if the new developer has taken to Python itself as a programming language, for developing AI applications. In other words, Python as an OOP based programming language provides the new developer with an API from the existing programming language, which indeed turns out to be beneficial, for the new Python developers.
One of the biggest plus points of Python, which attracts any developer, is it being platform independent. No major changes are required in the main source code to make your AI application platform independent. This saves a considerable amount of time for developers in testing on multiple operating systems. Therefore, it makes complete sense in hiring developers with expertise and exposure in Python for any AI-based projects.
A friend in need is a friend indeed! Python, like language, showcases every aspect of this important and well-known phrase through the quality of all its developers. In other words, being an open source programming language with a great developer community support, there are plenty of resources available that can get any developer to fix their issues and problems in no time. Python developers are known to work in tandem and get into fixing random coding issues when it comes to developing AI-based applications.
Being a programming language that is OOP based, Python also provides enhanced process control abilities. This adds up to increase its speed and productivity. When it comes to building complex multi-protocol, AI-based network applications, Python becomes a developer’s first and prime choice.
A diversified application range in Information Technology has driven companies such as in gaming, web frameworks, applications, language development, prototyping, and graphic design applications to name a few. Python is also interactive, portable, dynamic, and high level.
An AI-enabled system can have any combination of intelligence and goals. With the advances we are seeing in Artificial Intelligence, Cybersecurity has become more of a proactive process. Prominent examples where the implementation of AI has made a huge difference is smart home devices involved in heating and lighting activities, movie recommendation services like Pandora and Netflix, smart cars, security surveillance, news generation, fraud detection, video games, and online customer support. Hiring a competent and dedicated AI security expert could just be a parallel and correct step in our efforts to arrest the global threat of data insecurity. However, as days go by, and as technology is as rapidly changing as ever, Artificial Intelligence is getting to be a tricky challenge. Here is where Python is making the development process of AI-based projects a lot easier. Since Python offers the flexibility of shorter codes, developers are at a greater advantage and can find it easy to write code. Moreover, there are various built-in libraries in Python, which can make the AI-based application an advanced and robust one.
Published at DZone with permission of Mohamed Sathik Ali . See the original article here.
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