Artificial Intelligence has multiple uses in our daily lives. Facial recognition, purchase suggestions, advertising etc are everyday examples of its application.
To work in this area, it is necessary to know the tools used. So, in this article, you will get to know the best programming languages for artificial intelligence.
Python is one of the best languages for artificial intelligence due to its simple syntax and excellent readability , allowing a quick testing of complex machine learning algorithms. In addition, it has good tools for collaborative work.
It is also widely used for data analysis associated with big data , within the field of data science . It is not only for back-end applications, it is also applied in web development and front-end or full stack tasks .
It has several specific libraries for artificial intelligence. The availability of these materials makes Python one of the best languages for artificial intelligence.
Another positive point is that Python is versatility. It does not depend on a specific platform. Code written in Python can run on almost all operating systems, such as Windows, Linux, Mac OS and Unix. To port between platforms, you only need to change a few lines of code.
Many programmers choose Python also for its graphical results visualization options. When we work with complex areas within artificial intelligence, such as machine learning and deep learning, we often need to visualize the concepts to understand them better.
For this, Python has several libraries that allow the creation of graphs and histograms . Thus, we can have a better understanding and visualization of the code performance.
Java is one of the most widely used and loved programming languages. Much of its syntax is derived from C and C ++. One of its great advantages is being able to run on any platform that supports it without needing to recompile.
This is done thanks to the WORA (Write Once, Run Anywhere) principle, which in practice means that Java comes with an element called Java Virtual Machine, a virtual machine that uses the hardware to run the program.
We also have a garbage collector, which automatically excludes unused data and a community that is always ready to solve problems and answer questions.
It is one of the best languages for artificial intelligence, being used to create machine learning algorithms, search algorithms, artificial neural networks and genetic algorithms. It is a great choice for large projects . However there are some differences when compared to Python .
- C / C ++
The main reason C ++ is one of the best languages for artificial intelligence is its flexibility . This is because it is a low-level programming language, that is, its code is closer to the binary language used by computers.
This feature, in addition to object orientation , makes C ++ a very viable language for the development of artificial intelligence. For this reason, most deep learning and machine learning libraries are written in this language.
These peculiarities also contribute to the speed and efficiency of the code, since the conversion from programming language to machine language is faster. In the sense of performance, C ++ ends up distinguishing itself from Python.
In fact, it is considered by many the programming language with the fastest execution, being ideal for projects that depend on speed in response time .
All these characteristics show us its usefulness in solving complex problems of artificial intelligence, mainly in the fields of machine learning and artificial neural networks.
Within the programming area, Swift is well known for being used in the development of specific applications for iOS or MacOS . However, it gained a lot of prominence within the field of deep learning because of the Swift for Tensorflow (or S4TF, for short) library.
Other libraries, such as Swift AI, provide very interesting applications. We can create different artificial neural connections with support for deep learning, genetic algorithms, signal processing, among other features.
Compared to C, it is as fast as, reaching very satisfactory execution speeds , with the benefit of using much less memory and being easier to learn. Much of this is due to its powerful compiler, LLVM, which guarantees the speed of the code through efficient optimizations.