Most tools can be downloaded for free, including those created by IT companies. We offer programming libraries and programming languages that can be useful in AI modeling and have strong community support.

In the programming of artificial intelligence, languages and frameworks based on open source are particularly popular. The most common is Python , which has recently become one of the most widely used programming languages  in the world. Everything thanks to the ease of customization with a wide range of libraries for web applications, games, user interfaces and other applications.

On the other hand, AI is largely based on statistics. Similarly, the human brain works. The data we receive from the environment is often incomplete and inaccurate, and most decisions we make in a fraction of a second. It also involves learning to make mistakes and to draw conclusions from them. Artificial intelligence algorithms in the same way learn, for example, recognize objects in pictures.

For this reason, to begin programming SI, you need to know the basics of algebra and statistics. On the web we will find lectures on machine learning. I especially recommend those made available on YouTube by Professor  Andrew Ng  of Stanford University . It is a good idea to write the first programs in Octave . This free development environment is perfect for numerical calculations, which accelerates learning. Once you have mastered the concepts behind machine learning, you should be interested in the R language . It’s a programming language in which we can easily create a model and visualize it with more than 5,000 math libraries .

Machine learning is growing so fast through the open source community. Large companies provide their own tools to developers who want to improve their artificial intelligence algorithms. Google released its TensorFlow in 2015 , which today is one of the most popular GitHub projects. We may also be interested in the Microsoft Cognitive Toolkit , which is also developed under open source license, similarly to most of these development libraries. Other tools include Keras , which works with both the Microsoft and TensorFlow libraries. In Python, the SciKit-Learn library, which contains the most useful data analysis algorithms, is written .

All of these tools are supported by the community and by AI developers. Certainly artificial intelligence modeling is not an easy task and requires a lot of time. However, people who want to try their hand can count on many training materials and ready-made software tools.