Top 5 best Programming Languages for Artificial Intelligence field

programming languages

If it’s like you are working on a new artificial intelligence project and still have not decided which language you should use to program it, then you are at a right   place.

1. Python

Because of the simplicity, Python is considered to be at first in the list of all AI development languages. Python's syntaxes are very simple and easy to understand. Therefore, it can easily implement other AI algorithms. Compared with other languages such as Java, C++, or Ruby, Python requires short development time. Python supports programming styles which are object-oriented, functional and procedure-oriented. There are plenty of python libraries that facilitate our tasks. For instance: Numpy is a python library which helps us solve many scientific computations. We do have Pybrain, which is used in Python to use machine learning.

2. R
R is one of the most powerful language and environment for statistical analysis and manipulation of the data. Using R, we can easily produce well-designed plot of quality in the paper, including mathematical symbols and formulae where appropriate. Apart from being a language of general purpose, R has various packages such as RODBC, Gmodels, Class and Tm which are used in the field of machine learning. Such packages make it easy to apply machine learning algorithms to crack related business issues.

3. Lisp
Lisp is one of the oldest and best-suited AI development languages. It was invented in 1958 by Artificial Intelligence's father, John McCarthy. It has the capability to effectively process the symbolic knowledge.

It is also known for its excellent prototyping capabilities with automatic garbage collection, and fast dynamic development of new objects. The development cycle enables interactive evaluation of the expressions and function or file recompilation while the program is still running. Over the years, many of these features have spread into many other languages due to development, thereby impacting Lisp's uniqueness.

4. Prolog
When we speak about progress in the AI field, this language stays alongside Lisp. The features it provides include efficient pattern matching, structuring tree-based data, and automated backtracking. All of these features provide an extremely powerful and flexible programming structure. Prolog is commonly used for research projects, as well as for the creation of professional AI systems.

5. Java
Also, Java can be seen as a good choice for creating AI. Search algorithms, artificial neural networks and genetic programming have a lot to do with artificial intelligence. Java provides many advantages: ease of use, ease of debugging, package services, and easier work for large-scale projects, graphical data representation and better user experience. It also has Swing and SWT (the Simple Widget Toolkit) integrated. Those tools make graphics and interfaces look sophisticated and appealing.

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