How is Python related to Artificial Intelligence?

Today, all software programs and applications seek to save their users time and effort. This has been achieved through the use of programming languages ​​with artificial intelligence such as Python. The domain of programming lies in the success of the algorithms, which are included in the systems or codes to achieve the simulation of an artificial intelligence or AI (for its acronym). Over the years, programming languages ​​have evolved, allowing the appearance of new codes with better adaptation to the user and the environment, such as Python. Although Python is new compared to the years of existence of its closest competitors, it has managed to establish itself in a high position with high-level language.

To better understand how Python works and its relationship with artificial intelligence, it is necessary to understand its characteristics and comparison with other languages.

What is artificial intelligence?

The ability of all living beings to respond autonomously to a stimulus or situation can be considered intelligence. IN the case of human beings, we have a natural intelligence that is given by the interaction of our neurons in the brain, which store, process and respond to certain stimuli or instructions. IN the case of artificial intelligence, the Oracle digital portal defines it as those systems or machines that imitate human intelligence to execute some specific activity, where they acquire the ability to improve the performance of the task as they repeat it. An example of an Artificial Intelligence can be seen in the bots used by some companies to respond or chat with customers through certain platforms, speeding up service and reducing costs in waiting time and hired personnel.

Types of programming languages

When talking about programming languages, it is necessary to differentiate between the types of language and the progress made in their programming.

Low level languages.

They have better performance in actions and are more robust when the programs are well designed, but they require greater programming and code complexity, and a fairly advanced level of programming. Samples of these languages ​​are C, C++ and Objective-C.

Intermediate level languages.

They have a performance of the results of their code and the difficulty of programming it balanced between the two without ceasing to be a robust language. It has some tools that help the programmer to make code corrections, but leaves many execution decisions in the hands of the same programmer to optimize them. A sample of this kind of language is Java.

high level languages

These languages ​​allow a series of functions in their code, where the compiler of the program can make autonomous decisions, freeing the developer to make them. They tend to be less efficient languages ​​by assuming that decisions are not made by the developer in their code, but by the compiler, and they tend to be less human. But on the contrary, the chances of failure of these systems are lower. Samples of these languages ​​are Python and JavaScript. As defined above, artificial intelligence is based on autonomous learning or machine learning (it is a field of computer science that ensures that machines learn by themselves). This learning is achieved with pre-established codes in data libraries and with specific programming towards a function or task.

What is Python?

So, the Unipython portal defines Python as a high-level programming language, which has made it one of the most popular worldwide due to its versatility and ease of programming. Python currently has the largest community of developers who support the code and allow it to prove its strength against other languages ​​such as Java. Among the most outstanding features, Python has a wide library of libraries that allow obtaining various open-source resources applicable to artificial intelligence. These code libraries are far superior to what exists with Java; therefore, developers are always looking for what is done to solve situations instead of wasting time on existing coding. The programming language in Python is dynamic, which means that modules or applications can be created and tested faster than other languages. This also allows the developer to learn in less time.

Python Features

Python is an interpreted language, which does not need compilation. For this reason, the programmer can use the language directly in the program or application that he makes. Being a high-level language, Python can be used to solve complex situations, since the use of programming code will be less in terms of variables, arrays, and object handling. Another important feature of Python is automatic memory management, which allows you to analyze various situations in programming. There is also an availability of this language in all operating systems. Python has a large number of resources that allow artificial intelligence to learn. It also owns many online educational platforms through blog articles, books, courses, etc.

Python and artificial intelligence

Being Python, one of the most popular programming languages ​​in the world, and having less complexity in its code, they have made it the most acceptable means for creating artificial intelligence systems. Python libraries span areas of advanced scientific computing and machine learning such as NumPy, SciPy, and PyBrain. For this reason, its wide use in languages ​​for Artificial Intelligence. -The combination of the IDE (integrated development environment) with the flexibility of use on various operating system platforms, allows Python to check the codes with different algorithms more efficiently.

Python libraries to implement artificial intelligence

In the source code libraries of the various programming languages ​​oriented to Machine Learning, there are the algorithms that represent that preprogramed learning for certain actions. Among the most popular and useful Python libraries for artificial intelligence, the following stand out.

Display

Matplotlib: it is a purely graphical library, and it is the best known of Python. It allows you to create both digital and printed graphics.

Seaborn: is a library based on matplotlib, but oriented to the visualization of statistical data. It has a high-level graphical interface for statistical data.

Bokeh: Allows you to view data interactively in a web browser. Create dynamic, interactive charts that adjust in real time.

Numerical Calculation and Data Analysis

NumPy: Allows universal data structuring, ideal for analysis and interaction with algorithms. It implements various multidimensional vectors and arrays that can handle high volumes of data.

SciPy: Integrates very efficient and easy-to-use numerical routines. It complements the algorithms used in NumPy.

Pandas: Considered the most used library by data scientists. handles one- and two-dimensional data structure, highly recommended for financial and engineering operations

Numba: is a library that allows you to translate functions written in python into optimized machine code at the time of execution.

machine learning

Scikit-learn: This library is based on NumPy, SciPy and Matplotlib. It is used for the supervised and unsupervised machine learning that you implement.

deep learning

TensorFlow: is a library developed by Google, which allows numerical calculations using data flow diagrams to encode a graph. The nodes of this graph become mathematical operations and the edges represent tensors (multidimensional data arrays).

Keras: It is a high-level interface that allows working with neural networks. It is easier to use than TensorFlow. This interface is ideal for checking if the developments will obtain the expected results quickly. Keras uses other deep learning libraries (TensorFlow, CNTK or Theano) in a transparent way to do the work indicated.

PyTorch: It is a library developed by Facebook, which allows efficient numerical calculation. It has an improved processing quality in GPUs, which is why it is considered in the development of deep learning.

explainable AI

SHAP: is used to execute Explainable Artificial Intelligence (XAI for its acronym in English explainable Artificial Intelligence). It applies calculations from the field of game theory to obtain the variables that are most important in the predictions of machine learning techniques. This library allows us to understand how decisions are made in random forest models or neural networks.

Natural Language Processing

NLTK (Natural Language Toolkit): library used for natural language processing, and activities such as tokenization or exclusion of words in security data inputs. It represents one of the first libraries created in Python.

Gensim: is also a library for natural language processing. It is widely used for the construction and import of distributed vectors and the analysis of similarity between documents.

SpaCy: It is faster than the previous ones. It is very useful for preparing text for other machine learning tasks. It allows interfacing with other libraries TensorFlow, PyTorch, scikit-learn, Gensim, etc.

Jupyter Notebook: It is not a Python library, but it is widely used for handling scientific data. It is a web application for creating documents containing code, equations, visualizations, and text.

Anaconda: It is considered a set of Python distribution libraries for performing calculations, analysis, machine learning. Allows you to create various work environments.

Conclusions:

Artificial intelligence is an inseparable part of most computer application developments worldwide. Every day more ground is being gained in the creation of autonomous technologies through machine learning codes incorporated into these devices. There are various programming languages, which will have their greater or better utility depending on the level of development of the system by the programmer, or the level of independence of the module through the algorithms applied in it. Python is among the best high-level languages, since it has a wide range of data libraries and sources with established algorithms, and its programming code is much friendlier, allowing less extensive modules due to the use of artificial intelligence in them.