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Python has become one of the most widely used programming languages in the world mainly because it is extremely powerful, simple and has very good libraries that simplify development. But what is python, Python is a high-level, interpreted, object-oriented programming language. It was created by Guido van Rossum in 1991 and has become one of the most popular languages today due to its simplicity, readability and versatility.
Python is used in a wide variety of applications, including web development, data analysis, artificial intelligence and machine learning. In addition, Python has a large number of libraries and frameworks that facilitate the development of complex applications.
Python, among many of the areas in which it has been developed, is the development of web applications. Python in this area is mainly used for the development of the Back End (the server side) with different specialized libraries that are free to use.
Among the most outstanding libraries we have for this undertaking are:
The objective of machine learning is to create algorithms that allow the system to learn by itself from the data that is given to it, to specialize in this branch there are Machine Learning Engineer courses. These applications are not composed of the same type of development where we tell the program what and how to do what it should do, but the algorithms are improved from the data we feed it.
The Neural Networks are the processing units and try to simulate the behavior of our neurons. In this network the information will be received, they will learn to process it and this will allow them to generate results based on their learning.
A more practical example is when we receive ads depending on what we have consumed, either on YouTube, Facebook and other platforms, these networks are the ones that make the recommendations.
This machine learning process has several libraries that make the job much easier, such as:
In recent years the use of Python for Data Science has increased and has become one of the main languages for visualization and data processing today, which is to be expected. Py has extremely powerful libraries that allow the generation of visual representations such as the following:
The most used libraries for data analysis would be NumPy (the one used by most scientists who use Python to record their research) and Pandas (open source, fast and powerful tool that allows to analyze and manipulate data in a flexible and easy way).
For graph visualization we have a larger collection of libraries:
Python has also made its entry into the world of video games thanks mainly to the following libraries:
pygame -> The most active package for video game development within Python. With this library, Py can communicate with SDL (Simple DirectMedia Layer) to access multiple platforms. There may be a delay when updating the Python version as it must be compiled for each Python version and platform.
pyglet -> Based on OpenGL, this library makes up for the difficulties of pygames in the sense that, being completely written in Python, it does not need to be compiled every time there is a version change (except for the jump from Python 2 to Python 3).
turtle -> a module that comes with Python once you install it on the system and allows the creation of video games with simpler graphics and user interface.
Python has been used in medical research and data processing for the detection of diseases or anomalies in the patient's health.
Making use of different application branches that we have already mentioned, in the field of medicine and pharmacology, Python is capable of:
Among the libraries for the treatment and analysis of medical data, we find:
If we keep looking we will find that it can be used in many more branches, as can be, to mention a few:
As you can see, thanks to its power and flexibility, Python is rightly one of the most widely used programming languages in different branches of development and knowledge, ranging from purely technology-related functionalities to health and human welfare. Undoubtedly a language to be taken into account, if not mandatory, if we are in the world of programming.