Top 7 Artificial Intelligence And Machine Learning Programming Languages

  Solace  Infotech    March 3, 2021    33

 

Industries have started their revolution towards digital transformation and automation. Artificial intelligence and machine learning are the two main companions they can have for revolution. Most of you may wonder about the fear looming over AI. Despite the fact that AI has its flaws, it is not nothing to be feared. Various benefits of AI overpower its flaws to provide the best business solutions with most extreme accuracy. Adopting AI to your business operations can increase efficiency, agility and reduce costs. 

In future, we can see AI replicating human intelligence. For building efficient AI systems, you should know the programming languages and so here we came with the best programming languages with its features. Let’s have a look.

Also know the reasons to use artificial intelligence for business at- Why you should use artificial intelligence into your business?

Top 7 Artificial Intelligence and Machine Learning Programming Languages

1. Python-

Python is a leading programming language among artificial intelligence, machine learning and natural language processing. It is a widely used programming language due to its simple syntax and versatility. Near about 57% data scientists use Python regularly. Python is open-source and pretty handy in AI and ML. Means developers can easily modify it. Also there are various built-in Python libraries available for AI and ML. Data scientists use Scikit-Learn extensively for training models. Keras and tensorflow have gained a huge popularity in AI industry. One can build deep learning projects and software with PyTorch. Also, there are thousands of AI and ML models in Python. Simply, Python is pioneer of AI and ML.  

Features-

  • No need to recompile the source code, so developers can easily make some modifications and see the results.
  • Python is not dependent on any operating system. So one can develop machine learning on any of the OS available in the market.
  • This is a simple to read language, so any python developer can easily understand their peers’ code and modify, copy or share it. 
  • It has specific libraries for data visualization- for instance, Matplotlib, seaborn etc. One can make any type of graphs and charts with it.

Know the role of Python in artificial intelligence at- Role of Python in Artificial Intelligence (AI).

2. Prolog-

It is one of the oldest programming language that works with three elements- facts, rules and goals. Developer should define these three elements and then Prolog establishes relations between them to reach a certain conclusion by analyzing facts and rules. Algorithm implementation is carried out through logical inferences and searches. Prolog is a great language for developing AI systems since the solutions are logical and not just based on pre-existing statements. Also it is best to create chatbots,voice assistants and graphical user interfaces.

Features-

  • It can handle recursion and lists naturally. Also it gives the language an extra privilege.
  • Works well for natural language processing. ELIZA, the first chatbot, was developed using prolog.
  • This language is declarative in nature and it expresses logic in relations, represented as facts and rules.
  • Visual Prolog compiler is an optimized compiler that makes code compilation easier.
  • Visual Prolog Integrated Development Environment is Prolog’s IDE, that helps you to make apps and test them. 

3. R: A Statistical Language-

R is the best programming language in statistical computations. People also use it for data visualization. It has a command and IDEs like RStudio and Jupyter. It focuses on ease of use and offer different resources for handling libraries or drawing decent diagrams. 

Features-

  • It is open-source, cost free and can be modified and adapted according to user requirements and project.
  • This language can produce static graphics and high-quality visualization.
  • Doesn’t need a compiler because it is an interpreted language. 
  • Has big support from active community
  • Comprehensive R Archive Network or CRAN offers more than ten thousand packages to resolve machine learning problems.

4. Julia-

There are lots of artificial intelligence and machine learning programming languages. But none of them are some and efficient at the same time. Julia is a fast and it has easy syntax as compared to others. It is fast like C and easy syntax as Python? So data scientists prefer Julia for AI development.

Features-

  • Used for analysis of IoT data. 
  • It is handy in recognizing patterns and processing images.
  • It is a dynamic language close to Python but competes with static languages in terms of efficiency.
  • With Julia, one can call the C object code anytime

5. Java-

Java is one of the most popular programming languages having multitude of open-source libraries. As it is user-friendly and provides an independent platform, considered good for developing AI. Java is a standard and flexible programming language that offers easy code debugging, scalability, the ability to support large-scale enterprises and graphical representation of data. It is easy to learn, versatile and its Virtual Machine Technology enables the development of AI language on various platforms. This principle is called The “WORA” (Once Written Read/Run Anywhere).

Features-

  • Java is a strong object-oriented programming language to solve complex problems.
  • It has a machine learning library through which one can make machine learning and AI-based models using libraries.
  • Helps development of virus-free, tamper-free systems with stable Java feature. Authentication techniques are based on public-key encryption.
  • Java compiler is architectural-neutral. One can execute the compiled code on many processors.
  • This design feature helps developers to create apps that can run smoothly. 

6. Haskell-

Most of the people prefer Haskell to make Artificial Intelligence and Machine Learning models. It comes with attributes like list, Lazy evaluation and LogicT. Haskell provides an infinite data structure that is great for search trees. From the start, many find it disturbing to work with graphs, which is the language’s only drawback.

Features-

  • Haskell has an automatic memory management system which ensures memory safety.
  • It has a feature called garbage collection feature which makes it suitable for higher developer productivity.
  • Supports inspection and generation of the program’s abstract syntax tree.
  • Has a function named as Template Haskell and it is used to test compile-time and automate generation of boilerplate.

7. Lisp-

It is the oldest language among all other artificial intelligence and machine learning language. Lisp is AI-centered and has a huge use in AI development. It is neither fast nor easy. But for AI it does the work. Also, it is renowned as it focuses highly on architecture. Though Lisp’s popularity is not like Python, C++, Javascript, people still use it in particular needs of AI.

Features-

  • It is machine independent
  • Adapts easily to the solutions to unique needs.
  • Supports rapid prototyping
  • Allows dynamically updating of programs
  • Provides high-level debugging
  • Provides convenient macro system
  • Has a wide range of data types like lists, structures, objects, vectors, adjustable arrays, hash-tables and symbols.

Final Words-

Artificial intelligence and machine learning are making a huge change to every industry. Most of the businesses are thinking to adapt AI and ML technology for their businesses. If you are also one of them, you must know the list of languages and its features for an effective AI and ML development. 

 


 Article keywords:
artificial intelligence, machine learning, technology, tech

 


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