Artificial Intelligence has built an entirely new world of opportunities for developers to explore. AI allows Google to complete the question you ask, or Netflix to know what shows you’ll want to see next. It is used extensively by companies in customer service to improve workflows and employee productivity while driving self-service. There are programming languages like R, Java, Python, C# etc. which are ideal for AI-based projects.
The choice of one’s programming language depends on various factors like package ecosystems, ease to code, personal preferences etc. The skills of the developers matter more than any programming language. Python, a language favored by developers for a wide range of applications, but what makes Python ideal for projects involving AI?
Python, an Object Oriented, high level, interpreted programming language is a robust, developer friendly and highly useful, focusing on rapid application development (RAD) and don’t repeat yourself (DRY). It works perfectly to connect existing components together. Due to the ease of learning and adaptability of Python, it is one of the fastest growing languages. Python’s support and ever-evolving libraries make it a good choice for any projects, including AI.
The usage of Python is not limited to purpose. The growing popularity has allowed Python to enter into some of the most popular and complex processes like Artificial Intelligence (AI), Machine Learning (ML), natural language processing (NLP), data science etc.
Python has a huge stack of libraries and frameworks that facilitate coding and save development time. Libraries like NumPy, used for scientific computation, SciPy for advanced computation, and scikit-learn for data mining and data analysis, are the popular ones along with heavy-hitting frameworks as TensorFlow, CNTK, and Apache Spark. These libraries and frameworks are Python-first, while some, like PyTorch, are written specifically for Python, facilitating AI, ML, and deep learning.
Python is known for concise, readable code and ease of use, providing simplicity, particularly for new developers. This has several advantages for machine learning and deep learning. AI, ML and DL rely on complex algorithms and multi-stage workflows, so less complex the coding, the more they can focus on finding solutions to problems and achieving the goals of the project.
Python has a simple syntax resulting in faster in development than many programming languages, allowing the developer to quickly test algorithms without having to implement them. The easily readable code is invaluable for collaborative coding, or when machine learning or deep learning projects change hands between development teams. This is true if a project contains a great deal of custom business logic or third-party components.
Python is platform independent and provides the developer with the flexibility to provide an API from the existing programming language making it extremely flexible for the new Python developers. The same Python can run smoothly in any operating systems. Python is suitable for every purpose, be it scripting or OO approach. Python also works as a perfect backend language links various data structures together.
Python is popular among the large community of developers. The ease of learning is attracting a huge crowd to learn this language. Though AI Projects needs experience in programming, Python can smoothen the learning curve. It is practically more easy to look for Python developers than to hunt for LISP or R or Prolog programmers. Its extended libraries and active community with an ever developing and improving code have led it to be one of the popular languages of the day. Python also boasts a large, active community of developers who willing to offer help and support, which can be invaluable when dealing with such complex projects.
While many other programming languages can also be used in AI projects, Python is in fact at the cutting edge and should be given significant consideration. Therefore, Python is the primary choice for an AI product.
