The Best Programming Languages for Working with AI

You will require coding skills if you want to work in the field of artificial intelligence (AI). How do you begin? and Which programming language is ideal for AI? How about starting with these programming languages? I will list high-level overview of the top programming languages for artificial intelligence in this article, along with an explanation of their salient characteristics.

What Is Artificial Intelligence?

In the world of computer science, artificial intelligence is one of the most exciting and dynamic areas. As we speak, it has already begun to change the environment. The employment market is also at its hottest (see Gartner forecasts). AI strives to develop smart computer systems. Creating a computer system that can learn and do tasks independently is essentially what it is all about.

Contrarily, machine learning (ML) is concerned with the strategies and tactics used to enable a computer system to "learn" how to carry out specific activities and even anticipate specific outcomes without being explicitly programmed for it.

Best Programming Languages for AI Development

Here are the top programming languages for creating AI, along with a brief description of each.

Python

The most well-liked programming language for artificial intelligence is Python, which is also one of the trendiest languages right now. It is extremely appealing for rapid application development and usage as a scripting or glue language to tie existing components together due to its high-level, built-in data structures, dynamic typing, and dynamic binding. Python is a general-purpose, dynamically semantic, interpreted programming language.

What makes Python good for AI:

1. It makes working with the data simple thanks to a comprehensive collection of libraries for data analysis and manipulation, including Pandas.
2. TensorFlow and Keras are only two examples of the machine learning-specific libraries it contains.
3. It has reliable computational and scientific libraries like Scikit-Learn and NumPy.
4. Even microcontrollers can be programmed with it thanks to initiatives like Raspberry Pi, CircuitPython, and MicroPython.

Julia

Julia is a relatively new (it was released in 2012), brilliant, very fast, and flexible programming language for technical computing. Users of various technical computing environments will be familiar with Julia's syntax.

What makes Julia good for AI:

Julia is speedy, but she's also highly adaptable

Such as Flux, MLJ, and KNet, it has a variety of sophisticated machine learning libraries.

R

The R Foundation for Statistical Computation supports R, a programming language and open software environment for statistical computing and graphics. Since it's extensively used in government statistics, data mining, and the creation of statistical software and data analysis, the R language has become something of a lingua franca among statisticians. R has an active user base of roughly two million individuals globally, according to surveys of data miners, polls, and analyses of scientific literature databases.

What makes R good for AI:

In particular, statisticians were considered when designing it (unlike Python, which was designed as a general-purpose language).

The development of AI may benefit greatly from its various aspects, which include time series analysis, classification, clustering, and linear and nonlinear modeling.

JAVA

Java is a flexible and strong programming language that gives programmers the ability to build reliable, high-performance programs.

What makes Java good for AI:

It is swift, dependable, and provides excellent tool support (making it easy to develop complex AI applications quickly and efficiently).

It has been put to the test in several mission-critical applications.

It may be applied to desktop and mobile applications (using Android Studio).

Avoid These Programming Languages When Developing AI

While these languages may have their uses, they don't have anything to contribute to AI.

An ancient language, COBOL, was developed in the 1950s and 1960s. It is not really suitable for anything else because it was only intended for corporate purposes.

Another vintage language, FORTRAN, debuted in 1957. Similar to COBOL, it was created for use in applications related to science and engineering and is not really appropriate for anything else.

The 1970s saw the creation of the Pascal programming language, which is largely obsolete now outside of academia. Newer programming languages like Python have mainly replaced the beginner-friendly language, Basic.

What do the best languages for AI development have in common?

A few characteristics of the top programming languages for creating AI are shared by all of them:

1. Because they are all high-level languages, they are simple to learn and write code in.
2. You may leverage their diverse ecosystems of libraries and frameworks to construct AI.
3. You can get a ton of information and support online because they are all frequently utilized in the AI world.

What should I do first if I want to learn how to build AI?

I advise beginning with Python if you're just getting started. It's the most widely used language for creating AI, and learning it is not too difficult. You can switch to another language after learning Python if you need to.

Originally published here.