In this article, we intend to name the common programming languages used in artificial intelligence. It should be stated at the outset that programming languages are not specific to any particular branch and are used for anything that requires good speed, both in coding and in achieving results, etc, and can lead programmers to what they want with the least effort. Examples of criteria for choosing the appropriate programming language for AI are written below:
- The efficiency of the programming language
- Support for various libraries
- Community support
- Flexibility of the programming language
- Good results with minimal programming
Following is a list of the best programming languages, which includes:
To find the appropriate programming language for AI, it is important to consider the field in which we intend to work. The fields mentioned below have been introduced in this sheet. In this list, we address the most suitable programming languages for different branches of AI.
The most suitable programming languages in the field of machine learning:
- Python Programming Language:
Undoubtedly, Python holds the first rank as the best programming language in artificial intelligence. This programming language is centered around C++. Python is highly suitable for developing artificial intelligence and machine learning and can be said to be the most popular programming language in this field. The reasons for this popularity include:
- Abundant libraries
- High code readability
- Simple syntax: It has a very simple syntax so much so that it closely resembles the English language
- No need to recompile the source code: Any changes made to the program are quickly applied, and the results are displayed to the programmers.
- Support for various platforms: Python code can be executed on different platforms such as Windows, Mac, Linux, etc.
- Support from a large community and many other reasons
Python is an Object-Oriented and High-Level programming language with dynamic semantics integrated for web and application software development. Python is a very suitable programming language for those who are not familiar with programming and intend to start. Since Python is a multipurpose language, it can meet many needs and therefore can even be the only language required by the user. This language also has some disadvantages, some of which are:
- Difficulty in using other languages: Due to the ease of syntax and extensive libraries, migrating from this programming language to another language is difficult for someone who has become accustomed to it.
- Weak in mobile processing: Python has established and consolidated its position in many desktop and server platforms. However, it seems weak in mobile processing. For this reason, few mobile applications have been created with it. An example of a mobile application made with Python is ‘Carbonnelle’.
- Reduced speed: Python is considered fast for many web applications, but the use of a compiler instead of an interpreter during compilation is the reason for its reduced speed.
- Runtime errors: One of the problems and hassles for Python programmers is dealing with various errors they encounter during program execution. The solution to this problem is to perform various and numerous tests during programming and execution.
- Java Programming Language:
- A stable, reliable, and secure programming language known for its security.
- Java is designed to work with large applications and can easily integrate with other systems and technologies.
- Its speed is less than C++ or FORTRAN but much faster than Python.
- Java also allows developers to create complex and customized algorithms using this programming language, which makes working with large data and complex calculations easier.
- This programming language has many libraries for the field of machine learning, making it one of the choices in this field.
- C++ Programming Language:
C++ is an incredibly powerful programming language with low-level control, and its advantages in relation to machine learning include:
- High speed and efficiency, which make it one of the most powerful programming languages currently available.
- The ability to precisely control memory, which proves to be very useful in complex algorithms and high-level memory management.
- Numerous libraries for machine learning have been provided, which makes it a strong foundation for building models. It is noteworthy that many machine learning libraries in C++ are available in other languages like Python.
- The very high speed of this programming language makes it suitable for developing fast and efficient machine learning algorithms.
- Julia Programming Language:
- A high-speed programming language that, as a compiled language, has a high execution speed.
- Julia has a syntax close to the English language, which helps ease learning and understanding.
- It has strong libraries and tools that make the construction and optimization of machine learning models efficient and effective.
- This programming language is designed for scientific computations and analysis of large data sets.
- Julia can be executed on various platforms.
- JavaScript Programming Language:
JavaScript is a browser-based programming language used for machine learning in web environments. Its advantages include:
- This programming language is widely used in web development, which allows it to easily integrate with web technologies like HTML and CSS.
- It includes powerful libraries that have several specific libraries in the field of machine learning.
- JavaScript can be used for both Front end and Back end development.
- This programming language can be executed on a browser, which allows it to quickly and easily run an artificial intelligence program on the browser.
- JavaScript has a high scalability potential, which enables it to create programs that can handle large amounts of data. This programming language can be used on any device or operating system.
The most suitable programming languages in the field of neural networks:
Notice: The programming languages Python, Java, and C++ have been introduced above in the section (The most suitable programming languages in the field of machine learning).
- Python
- Java
- C++
- R: A powerful programming language for statistical analysis and data visualization. This programming language is a suitable option for projects that require manipulation and heavy analysis of data. In addition, some of the features of this programming language include:
- You can build a neural network from scratch with this programming language and check its output at every stage.
- R offers several packages for implementing neural networks, providing various facilities for building and training a neural network.
- This programming language helps you develop deeper learning models in this field.
- Prolog: An old programming language that is suitable for neural networks for reasons such as:
- The pattern matching and automatic backtracking capabilities of this programming language make Prolog suitable for developing complex algorithms that involve logical requests based on rules.
- Unlike imperative languages that follow instructions, Prolog is a declarative language and focuses on the relationships between facts and rules.
- The Neural Markov Prolog (NMP) language, based on both Markov logic and Prolog, is proposed as a tool for creating a bridge between first-order logic and neural network design, as well as allowing easy construction and presentation of architectures for images, text, relational databases, or other types of data or their combinations.
The most suitable programming languages in the field of robotics:
Notice: The programming languages Python, Java, and C++ have been introduced above in the section (The most suitable programming languages in the field of machine learning).
- Python
- Java
- C++
- C#:A language that is used and applicable in many robotics programs. Some of its advantages include:
- C# provides a multi-purpose environment that, with the .NET framework, allows developers to use extensive libraries for tasks such as complex mathematical computations, data processing, and even AI integration.
- Visual Studio is an IDE from Microsoft, one of the most advanced, which makes debugging, testing, and launching robotics programs very easy.
- Robots that run on Windows can benefit from optimal support by C#.
- Programs developed with C# are highly secure and powerful.
- C# allows for the simplest form of motor control.
- In robotics, robots often use sensors to collect data. C# can read this data well.
- It enables integration with computer vision and machine learning.
- Matlab: A programming language with a powerful system for data analysis. Some of the advantages of Matlab include:
- It allows the programmer to quickly write usable code.
- Matlab’s robotics toolbox is widely used.
- It provides the possibility of complex simulations.
- With this programming language, you can develop robotics programs with deep and reinforcement learning. These techniques provide greater accuracy for robot perception and require less human intervention in decision-making.
- Lisp: This programming language has always been one of the languages used in the field of robotics since the beginning of artificial intelligence. Lisp is a high-level programming language that can be useful in complex parts of robotics. Some of the advantages of this programming language include:
- It is a symbolic programming language, which allows programmers to easily work with structured data.
- It provides the possibility of high-level debugging.
- Lisp integrates well with the Robot Operating System (ROS), which is why it can be used to develop complex robotic systems.
The most suitable programming languages in the field of expert systems:
Notice: The programming languages Python and Java have been introduced in the section (the most suitable programming languages in the field of machine learning), the programming languages Prolog and R in the section (the most suitable programming languages in the field of neural networks), and Lisp in the section (the most suitable programming languages in the field of robotics).
- Python
- Java
- R
- Prolog
- Lisp
The most suitable programming languages in the field of fuzzy logic:
Notice: The programming languages Python and Java have been introduced in the section (the most suitable programming languages in the field of machine learning) and the programming language Prolog in the section (the most suitable programming languages in the field of fuzzy logic).
- Python
- Java
- Prolog
The most suitable programming languages in the field of natural language processing:
Notice: The programming languages Python, Java, C++, and Julia have been introduced in the section (the most suitable programming languages in the field of machine learning) and the programming language R in the section (the most suitable programming languages in the field of neural networks).
- Python
- Java
- C++
- Julia
- R
Conclusion: It is important to choose the right programming language for the task at hand. If you look at the list we have prepared, some languages are multi-purpose and can be used in several branches of artificial intelligence. For example, the Python programming language was among the most suitable in all the mentioned branches. In this article, we have only introduced these programming languages. However, which one is better and which is more suitable for you is a matter for you to decide by reviewing and concluding.
