Most Popular Programs Used in Artificial Intelligence !!!

Most Popular Programs Used in Artificial Intelligence !!!

Artificial intelligence coding occupies an important place in today’s technology. Inventions made in this field are increasing day by day. At this point, they have difficulty in choosing where and how to start and which programming language to use. You can use any language for artificial intelligence programming. Whatever software you want to develop in this area, you should choose a language accordingly.

There are also programming languages ​​that are suitable for use in artificial intelligence programming. By teaching various software languages ​​under the name of coding, including in schools, students take the basis of this technology at an early age.

Therefore, this article aims to provide you with a suitable AI programming language. “What language is used for artificial intelligence?”


Python programming language, Python is the most preferred programming language in Artificial Intelligence programming. It is one of the foremost reasons for popularity due to easy coding and low possibility of making mistakes. It started to be developed in 1991 and gradually climbed to the top of the list. There are versions of Python2x and Python3x developed by the Python software foundation. Python can run on any platform. (Unix, Linux, Windows, Mac, Amiga, Symbian)

Python Features !!!

  • Easy to learn – Python has a few keywords, simple structure, and clear syntax. This allows students to learn the language quickly.
  • Easy to read – Python code is clearer and clearer.
  • Easy to maintain – Python source code is very easy to maintain.
  • Comprehensive standard libraries – Most Python libraries are very portable and cross-platform compatible with UNIX, Windows, and Macintosh.
  • Interactive mode – Python supports interactive mode that allows interactive testing and debugging of code snippets.
  • Portable – Python can run on a variety of hardware platforms and has the same interface on all platforms.
  • Extensible – We can add low-level modules to the Python interpreter. These modules allow programmers to add or customize their tools more efficiently.
  • Database -Python provides an interface to all major commercial databases.
  • GUI programming -Python supports many system calls, libraries, and GUI applications that can be created and ported to Windows systems such as Windows MFC, Macintosh, and Unix X Window System.


Lisp programming language is one of the oldest programs in use. It was first released in 1958 by John McCarthy. It was given as a programming course to undergraduate students at MIT for one semester. He is known by John McCarthy, known as the father of artificial intelligence, for his influence on his capacity to process symbolic information. Over the years, is it the most effective programming language in artificial intelligence?


Prolog programming language, Another favorite of artificial intelligence software developers is prolog. It is the closest programming language to Lisp in terms of ease of use. It is preferred for artificial intelligence because it makes queries between relationships. It supports users’ basic mechanisms such as pattern development, tree data structuring, and automatic backtracking required for AI programming. In addition to being widely used in artificial intelligence projects, Prolog is also used to create medical systems.


C ++ programming language is the fastest compiling language and it is used especially for game programming. It has been used for years and is very useful for artificial intelligence programming. It allows programming on the object. It can be used in statistical techniques such as neural networks.


The Java programming language is the whole of the software produced by Sun Microsystems that helps to develop artificial intelligence. Artificial intelligence is one of the popular languages ​​in use, which is not at a high level according to Lisp and Prolog! But besides allowing programming on the object, it has the features required for artificial intelligence. It is currently in the 1st place in programming languages ​​in 2020.


The R programming language is effective for data analysis and goals. You can write well-designed quality programs with R. You can use mathematical formulas and symbols. It is used for machine learning with artificial intelligence.

Artificial Intelligence Libraries
– Numpy
– Matplotlib
– Python
– Scikit-Learn
– Tensorflow
– Pylearn2
– Orange3
– Pymc3
– PyBrain
– Fuel
– Annoy
– Keras


We shared the list of libraries used for artificial intelligence with you above. Let’s examine the most preferred ones of these libraries …


Pandas library is an open-source library that provides high performance, data structures, and data analysis tools for the Python programming language. It is used to open Text and CSV files and to reach the desired result by reading the data in it. Pandas is well optimized for speed and responds very quickly.

We can import this library with the “import pandas as PD” code block.


Numpy library is a math library that applies scientific calculations quickly. It can operate with multi-dimensional arrays and matrices. It is open-source software.

We can import this library with the “import NumPy as np” code block.


Tensorflow library is an end-to-end open-source platform for data flow and machine learning. It offers us the opportunity to create easy models. Tensorflow has been developed by the Google Brain team for Google users.

We can import this library with the “import TensorFlow as tf” code block.

The Matplotlib library is a drawing library for Numpy, together with the Python programming language. It has an active development community. With this library, you can make examples such as histogram, scatter plot, 3D drawing, 3-D graph, image graph. It has a MATLAB-like interface.

We can import this library with the “import matplotlib.pyplot as plt” code block.


Keras library is an open-source neural network library written in Python. Keras and Tensorflow libraries can work together. It is useful for fast results in combination with deep neural networks.

We can import this library with the “import TensorFlow as tf” “from TensorFlow import Keras” code block.

Today, we examined the programming language and libraries you should use when developing projects related to artificial intelligence. You can choose the one according to you.



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